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8
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Coordinating Lead Authors:
Ralph Sims (New Zealand), Roberto Schaeffer (Brazil)
Lead Authors:
Felix Creutzig (Germany), Xochitl Cruz-Núñez (Mexico), Marcio D’Agosto (Brazil), Delia Dimitriu
(Romania / UK), Maria Josefina Figueroa Meza (Venezuela / Denmark), Lew Fulton (USA), Shigeki
Kobayashi (Japan), Oliver Lah (Germany), Alan McKinnon (UK / Germany), Peter Newman
(Australia), Minggao Ouyang (China), James Jay Schauer (USA), Daniel Sperling (USA), Geetam
Tiwari (India)
Contributing Authors:
Adjo A. Amekudzi (USA), Bruno Soares Moreira Cesar Borba (Brazil), Helena Chum (Brazil / USA),
Philippe Crist (France / USA), Han Hao (China), Jennifer Helfrich (USA), Thomas Longden
(Australia / Italy), André Frossard Pereira de Lucena (Brazil), Paul Peeters (Netherlands), Richard
Plevin (USA), Steve Plotkin (USA), Robert Sausen (Germany)
Review Editors:
Elizabeth Deakin (USA), Suzana Kahn Ribeiro (Brazil)
Chapter Science Assistant:
Bruno Soares Moreira Cesar Borba (Brazil)
This chapter should be cited as:
Sims R., R. Schaeffer, F. Creutzig, X. Cruz-Núñez, M. D’Agosto, D. Dimitriu, M. J. Figueroa Meza, L. Fulton, S. Kobayashi, O.
Lah, A. McKinnon, P. Newman, M. Ouyang, J. J. Schauer, D. Sperling, and G. Tiwari, 2014: Transport. In: Climate Change
2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovern-
mental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler,
I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)].
Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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Contents
Executive Summary � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 603
8�1 Freight and passenger transport (land, air, sea and water) � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 605
8�1�1 The context for transport of passengers and freight
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 606
8�1�2 Energy demands and direct / indirect emissions
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 608
8�2 New developments in emission trends and drivers � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 610
8�2�1 Trends
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 611
8.2.1.1 Non-CO
2
greenhouse gas emissions, black carbon, and aerosols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 611
8�2�2 Drivers
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 612
8�3 Mitigation technology options, practices and behavioural aspects � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 613
8�3�1 Energy intensity reduction — incremental vehicle technologies
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 613
8.3.1.1 Light duty vehicles
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613
8.3.1.2 Heavy-duty vehicles
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613
8.3.1.3 Rail, waterborne craft, and aircraft
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614
8�3�2 Energy intensity reduction — advanced propulsion systems
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 614
8.3.2.1 Road vehicles — battery and fuel cell electric-drives
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614
8.3.2.2 Rail, waterborne craft, and aircraft
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 615
8�3�3 Fuel carbon intensity reduction
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 615
8�3�4 Comparative analysis
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 616
8�3�5 Behavioural aspects
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 616
8�4 Infrastructure and systemic perspectives� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 618
8�4�1 Path dependencies of infrastructure and GHG emission impacts
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 618
8�4�2 Path dependencies of urban form and mobility
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 619
8.4.2.1 Modal shift opportunities for passengers
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 620
8.4.2.2 Modal shift opportunities for freight
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621
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8�5 Climate change feedback and interaction with adaptation � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 622
8�5�1 Accessibility and feasibility of transport routes
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 622
8�5�2 Relocation of production and reconfiguration of global supply chains
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 622
8�5�3 Fuel combustion and technologies
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 622
8�5�4 Transport infrastructure
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 623
8�6 Costs and potentials � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 630
8�7 Co-benefits, risks and spillovers � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 630
8�7�1 Socio-economic, environmental, and health effects
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 633
8�7�2 Technical risks and uncertainties
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 633
8�7�3 Technological spillovers
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 633
8�8 Barriers and opportunities � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 633
8�8�1 Barriers and opportunities to reduce GHGs by technologies and practices
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 633
8�8�2 Financing low-carbon transport
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 636
8�8�3 Institutional, cultural, and legal barriers and opportunities
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 636
8�9 Sectoral implications of transformation pathways and sustainable development � � � � � � � � � � � � � � 637
8�9�1 Long term stabilization goals — integrated and sectoral perspectives
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 637
8�9�2 Sustainable development
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 641
8�10 Sectoral policies � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 642
8�10�1 Road transport
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 642
8�10�2 Rail transport
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 645
8�10�3 Waterborne transport
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 645
8�10�4 Aviation
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 646
8�10�5 Infrastructure and urban planning
� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 647
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8�11 Gaps in knowledge and data � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 647
8�12 Frequently Asked Questions � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 647
References � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 650
Dedication to Lee Schipper
This Transport chapter is dedicated to the memory of Leon Jay
(Lee) Schipper. A leading scientist in the field of energy research
with emphasis on transport, Lee died on 16 August 2011 at the
age of 64. He was a friend and colleague of many of the Chapter
authors who were looking forward to working with him in his
appointed role as Review Editor. Lee’s passing is a great loss to
the research field of transport, energy, and the environment and
his expertise and guidance in the course of writing this chapter
was sorely missed by the author team, as were his musical tal-
ents.
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Chapter 8
Executive Summary
Reducing global transport greenhouse gas (GHG) emissions
will be challenging since the continuing growth in passenger
and freight activity could outweigh all mitigation measures
unless transport emissions can be strongly decoupled from GDP
growth (high confidence).
The transport sector produced 7.0 GtCO
2
eq of direct GHG emissions
(including non-CO
2
gases) in 2010 and hence was responsible for
approximately 23 % of total energy-related CO
2
emissions (6.7 GtCO
2
)
[8.1]. Growth in GHG emissions has continued since the Fourth Assess-
ment Report (AR4) in spite of more efficient vehicles (road, rail, water
craft, and aircraft) and policies being adopted. (robust evidence, high
agreement) [Section 8.1, 8.3]
Without aggressive and sustained mitigation policies being imple-
mented, transport emissions could increase at a faster rate than emis-
sions from the other energy end-use sectors and reach around 12 Gt
CO
2
eq / yr by 2050. Transport demand per capita in developing and
emerging economies is far lower than in Organisation for Economic
Co-operation and Development (OECD) countries but is expected
to increase at a much faster rate in the next decades due to rising
incomes and development of infrastructure. Analyses of both sectoral
and integrated model scenarios suggest a higher emission reduction
potential in the transport sector than the levels found possible in AR4
and at lower costs. Since many integrated models do not contain a
detailed representation of infrastructural and behavioural changes,
their results for transport can possibly be interpreted as conserva-
tive. If pricing and other stringent policy options are implemented in
all regions, substantial decoupling of transport GHG emissions from
gross domestic product (GDP) growth seems possible. A strong slow-
ing of light-duty vehicle (LDV) travel growth per capita has already
been observed in several OECD cities suggesting possible saturation.
(medium evidence, medium agreement) [8.6, 8.9, 8.10]
Avoided journeys and modal shifts due to behavioural change,
uptake of improved vehicle and engine performance technolo-
gies, low-carbon fuels, investments in related infrastructure,
and changes in the built environment, together offer high miti-
gation potential (high confidence).
Direct (tank-to-wheel) GHG emissions from passenger and freight
transport can be reduced by:
• avoiding journeys where possible — by, for example, densifying
urban landscapes, sourcing localized products, internet shopping,
restructuring freight logistics systems, and utilizing advanced infor-
mation and communication technologies (ICT);
• modal shift to lower-carbon transport systems — encouraged by
increasing investment in public transport, walking and cycling
infrastructure, and modifying roads, airports, ports, and railways
to become more attractive for users and minimize travel time and
distance;
• lowering energy intensity (MJ / passenger km or MJ / tonne km) — by
enhancing vehicle and engine performance, using lightweight
materials, increasing freight load factors and passenger occupancy
rates, deploying new technologies such as electric 3-wheelers;
• reducing carbon intensity of fuels (CO
2
eq / MJ) — by substituting oil-
based products with natural gas, bio-methane, or biofuels, electric-
ity or hydrogen produced from low GHG sources.
In addition, indirect GHG emissions arise during the construction of
infrastructure, manufacture of vehicles, and provision of fuels (well-to-
tank). (robust evidence, high agreement) [8.3, 8.4, 8.6 and Chapters
10, 11, 12]
Both short- and long-term transport mitigation strategies are
essential if deep GHG reduction ambitions are to be achieved
(high confidence).
Short-term mitigation measures could overcome barriers to low-car-
bon transport options and help avoid future lock-in effects resulting,
for example, from the slow turnover of vehicle stock and infrastructure
and expanding urban sprawl. Changing behaviour of consumers and
businesses will likely play an important role but is challenging and the
possible outcomes, including modal shift, are difficult to quantify. Busi-
ness initiatives to decarbonize freight transport have begun, but need
support from policies that encourage shifting to low-carbon modes
such as rail or waterborne options where feasible, and improving logis-
tics. The impact of projected growth in world trade on freight trans-
port emissions may be partly offset in the near term by more efficient
vehicles, operational changes, ‘slow steaming’ of ships, eco-driving and
fuel switching. Other short-term mitigation strategies include reducing
aviation contrails and emissions of particulate matter (including black
carbon), tropospheric ozone and aerosol precursors (including NO
x
)
that can have human health and mitigation co-benefits in the short
term. (medium evidence, medium agreement) [8.2, 8.3, 8.6, 8.10]
Methane-based fuels are already increasing their share for road
vehicles and waterborne craft. Electricity produced from low-car-
bon sources has near-term potential for electric rail and short- to
medium-term potential as electric buses, light-duty and 2-wheel
road vehicles are deployed. Hydrogen fuels from low-carbon sources
constitute longer-term options. Gaseous and liquid-biofuels can pro-
vide co-benefits. Their mitigation potential depends on technology
advances (particularly advanced ‘drop-in’ fuels for aircraft and other
vehicles) and sustainable feedstocks. (medium evidence, medium
agreement) [8.2, 8.3]
The technical potential exists to substantially reduce the current CO
2
eq
emissions per passenger or tonne kilometre for all modes by 2030
604604
Transport
8
Chapter 8
and beyond. Energy efficiency and vehicle performance improvements
range from 30 – 50 % relative to 2010 depending on mode and vehicle
type. Realizing this efficiency potential will depend on large invest-
ments by vehicle manufacturers, which may require strong incentives
and regulatory policies in order to achieve GHG emissions reduction
goals. (medium evidence, medium agreement) [8.3, 8.6, 8.10]
Over the medium-term (up to 2030) to long-term (to 2050 and
beyond), urban (re)development and investments in new infrastruc-
ture, linked with integrated urban planning, transit-oriented develop-
ment and more compact urban form that supports cycling and walking
can all lead to modal shifts. Such mitigation measures could evolve
to possibly reduce GHG intensity by 20 – 50 % below 2010 baseline by
2050. Although high potential improvements for aircraft efficiency are
projected, improvement rates are expected to be slow due to long air-
craft life, and fuel switching options being limited, apart from biofu-
els. Widespread construction of high-speed rail systems could partially
reduce short-to-medium-haul air travel demand. For the transport sec-
tor, a reduction in total CO
2
eq emissions of 15 – 40 % could be plau-
sible compared to baseline activity growth in 2050. (medium evidence,
medium agreement) [8.3, 8.4, 8.6, 8.9, 12.3, 12.5]
Barriers to decarbonizing transport for all modes differ across
regions, but can be overcome in part by reducing the marginal
mitigation costs (medium evidence, medium agreement).
Financial, institutional, cultural, and legal barriers constrain low-car-
bon technology uptake and behavioural change. All of these barri-
ers include the high investment costs needed to build low-emissions
transport systems, the slow turnover of stock and infrastructure, and
the limited impact of a carbon price on petroleum fuels already heav-
ily taxed. Other barriers can be overcome by communities, cities, and
national governments which can implement a mix of behavioural mea-
sures, technological advances, and infrastructural changes. Infrastruc-
ture investments (USD / tCO
2
avoided) may appear expensive at the
margin, but sustainable urban planning and related policies can gain
support when co-benefits, such as improved health and accessibility,
can be shown to offset some or all of the mitigation costs. (medium
evidence, medium agreement) [8.4, 8.7, 8.8]
Oil price trends, price instruments on emissions, and other measures
such as road pricing and airport charges can provide strong economic
incentives for consumers to adopt mitigation measures. Regional dif-
ferences, however, will likely occur due to cost and policy constraints.
Some near term mitigation measures are available at low marginal
costs but several longer-term options may prove more expensive. Full
societal mitigation costs (USD / tCO
2
eq) of deep reductions by 2030
remain uncertain but range from very low or negative (such as effi-
ciency improvements for LDVs, long-haul heavy-duty vehicles (HDVs)
and ships) to more than 100 USD / tCO
2
eq for some electric vehicles,
aircraft, and possibly high-speed rail. Such costs may be significantly
reduced in the future but the magnitude of mitigation cost reductions
is uncertain. (limited evidence, low agreement) [8.6, 8.9]
There are regional differences in transport mitigation pathways
with major opportunities to shape transport systems and infra-
structure around low-carbon options, particularly in developing
and emerging countries where most future urban growth will
occur (robust evidence, high agreement).
Transport can be an agent of sustained urban development that priori-
tizes goals for equity and emphasizes accessibility, traffic safety, and
time-savings for the poor while reducing emissions, with minimal det-
riment to the environment and human health. Transformative trajecto-
ries vary with region and country due to differences in the dynamics
of motorization, age and type of vehicle fleets, existing infrastructure,
and urban development processes. Prioritizing access to pedestrians
and integrating non-motorized and public transit services can result
in higher levels of economic and social prosperity in all regions. Good
opportunities exist for both structural and technological change around
low-carbon transport systems in most countries but particularly in fast
growing emerging economies where investments in mass transit and
other low-carbon transport infrastructure can help avoid future lock-
in to carbon intensive modes. Mechanisms to accelerate the transfer
and adoption of improved vehicle efficiency and low-carbon fuels to all
economies, and reducing the carbon intensity of freight particularly in
emerging markets, could offset much of the growth in non-OECD emis-
sions by 2030. It appears possible for LDV travel per capita in OECD
countries to peak around 2035, whereas in non-OECD countries it will
likely continue to increase dramatically from a very low average today.
However, growth will eventually need to be slowed in all countries.
(limited evidence, medium agreement) [8.7, 8.9]
A range of strong and mutually-supportive policies will be
needed for the transport sector to decarbonize and for the co-
benefits to be exploited (robust evidence, high agreement).
Decarbonizing the transport sector is likely to be more challenging
than for other sectors, given the continuing growth in global demand,
the rapid increase in demand for faster transport modes in developing
and emerging economies, and the lack of progress to date in slowing
growth of global transport emissions in many OECD countries. Trans-
port strategies associated with broader non-climate policies at all gov-
ernment levels can usually target several objectives simultaneously to
give lower travel costs, improved mobility, better health, greater energy
security, improved safety, and time savings. Realizing the co-benefits
depends on the regional context in terms of economic, social, and polit-
ical feasibility as well as having access to appropriate and cost-effective
advanced technologies. (medium evidence, high agreement) [8.4, 8.7]
In rapidly growing developing economies, good opportunities exist for
both structural and technological change around low-carbon trans-
port. Established infrastructure may limit the options for modal shift
and lead to a greater reliance on advanced vehicle technologies. Policy
changes can maximize the mitigation potential by overcoming the bar-
riers to achieving deep carbon reductions and optimizing the synergies.
Pricing strategies, when supported by education policies to help cre-
605605
Transport
8
Chapter 8
ate social acceptance, can help reduce travel demand and increase the
demand for more efficient vehicles (for example, where fuel economy
standards exist) and induce a shift to low-carbon modes (where good
modal choice is available). For freight, a range of fiscal, regulatory, and
advisory policies can be used to incentivize businesses to reduce the
carbon intensity of their logistical systems. Since rebound effects can
reduce the CO
2
benefits of efficiency improvements and undermine a
particular policy, a balanced package of policies, including pricing ini-
tiatives, could help to achieve stable price signals, avoid unintended
outcomes, and improve access, mobility, productivity, safety, and
health. (medium evidence, medium agreement) [8.7, 8.9, 8.10]
Knowledge gaps in the transport sector
There is a lack of comprehensive and consistent assessments of the
worldwide potential for GHG emission reduction and especially costs
of mitigation from the transport sector. Within this context, the poten-
tial reduction is much less certain for freight than for passenger modes.
For LDVs, the long-term costs and high energy density potential for
on-board energy storage is not well understood. Also requiring evalua-
tion is how best to manage the tradeoffs for electric vehicles between
performance, driving range and recharging time, and how to create
successful business models.
Another area that requires additional research is in the behavioural
economic analysis of the implications of norms, biases, and social
learning in decision making, and of the relationship between trans-
port and lifestyle. For example, how and when people will choose to
use new types of low-carbon transport and avoid making unnecessary
journeys is unknown. Consequently, the outcomes of both positive and
negative climate change impacts on transport services and scheduled
timetables have not been determined, nor have the cost-effectiveness
of carbon-reducing measures in the freight sector and their possible
rebound effects. Changes in the transport of materials as a result of
the decarbonization of other sectors and adaptation of the built envi-
ronment are unknown. [8.11]
8.1 Freight and passenger
transport (land, air,
sea and water)
Greenhouse gas (GHG) emissions from the transport sector have more
than doubled since 1970, and have increased at a faster rate than any
other energy end-use sector to reach 7.0 Gt CO
2
eq in 2010
1
(IEA, 2012a;
1
CO
2
eq units are used throughout this chapter for direct emissions wherever
feasible, although this is not always the case in some literature that reports CO
2
emissions only. For most transport modes, non-CO
2
gases are usually less than
5 % of total vehicle emissions.
JRC / PBL, 2013; see Annex II.8). Around 80 % of this increase has come
from road vehicles (see Figure 8.1). The final energy consumption for
transport reached 28 % of total end-use energy in 2010 (IEA, 2012b), of
which around 40 % was used in urban transport (IEA, 2013). The global
transport industry (including the manufacturers of vehicles, providers
of transport services, and constructors of infrastructure) undertakes
research and development (R&D) activities to become more carbon
and energy efficient. Reducing transport emissions will be a daunting
task given the inevitable increases in demand and the slow turnover
and sunk costs of stock (particularly aircraft, trains, and large ships)
and infrastructure. In spite of a lack of progress to date, the transition
required to reduce GHG emissions could arise from new technologies,
implementation of stringent policies, and behavioural change.
Key developments in the transport sector since the Intergovernmen-
tal Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)
(IPCC, 2007) include:
• continued increase in annual average passenger km per capita,
but signs that LDV
2
ownership and use may have peaked in some
OECD countries (8.2);
• deployment of technologies to reduce particulate matter and black
carbon, particularly in OECD countries (8.2);
• renewed interest in natural gas as a fuel, compressed for road
vehicles and liquefied for ships (8.3);
• increased number of electric vehicles (including 2-wheelers) and
bus rapid transit systems, but from a low base (8.3);
• increased use of sustainably produced biofuels including for avia-
tion (8.3, 8.10);
• greater access to mobility services in developing countries (8.3,
8.9);
• reduced carbon intensity of operations by freight logistics compa-
nies, the slow-steaming of ships, and the maritime industry impos-
ing GHG emission mandates (8.3, 8.10);
• improved comprehension that urban planning and developing
infrastructure for pedestrians, bicycles, buses and light-rail can
impact on modal choice while also addressing broader sustainabil-
ity concerns such as health, accessibility and safety (8.4, 8.7);
• better analysis of comparative passenger and freight transport
costs between modes (8.6);
• emerging policies that slow the rapid growth of LDVs especially
in Asia, including investing in non-motorized transport systems
(8.10);
• more fuel economy standards (MJ / km) and GHG emission vehicle
performance standards implemented for light and heavy duty vehi-
cles (LDVs and HDVs) (8.10); and
• widely implemented local transport management policies to
reduce air pollution and traffic congestion (8.10).
2
LDVs are motorized vehicles (passenger cars and commercial vans) below
approximately 2.5 – 3.0 t net weight with HDVs (heavy duty vehicles or “trucks”
or “lorries”) usually heavier.
606606
Transport
8
Chapter 8
Figure 8�1 | Direct GHG emissions of the transport sector (shown here by transport mode) rose 250 % from 2.8 Gt CO
2
eq worldwide in 1970 to 7.0 Gt CO
2
eq
in 2010 (IEA, 2012a;
JRC / PBL, 2013; see Annex II.8).
Note: Indirect emissions from production of fuels, vehicle manufacturing, infrastructure construction etc. are not included.
2010200520001995199019851980
19751970
Total Direct and Indirect 2.9
(Total Direct 2.8)
Total Direct and Indirect 4.9
(Total Direct 4.7)
Total Direct
and Indirect 7.1
(Total Direct 7.0)
0
1
2
3
4
5
6
7
8
Indirect Emissions from Electricity Generation
Road
Rail
Pipeline etc.
HFC & Indirect N
2
0
International Aviation
Domestic Aviation
International & Coastal Shipping
Domestic Waterborne
GHG Emissions [GtCO
2
eq/yr]
100%
1.12%
5.55%
72.06%
2.38%
+2.11%
1.60%
2.16%
6.52%
4.10%
9.26%
1.91%
+2.83%
71.00%
3.34%
3.45%
5.39%
5.94%
2.09%
7.66%
3.26%
11.66%
5.71%
1.38%
2.81%
9.78%
59.85%
+2,71%
For each mode of transport, direct GHG emissions can be decomposed
3
into:
• activity — total passenger-km / yr or freight tonne-km / yr having a
positive feedback loop to the state of the economy but, in part,
influenced by behavioural issues such as journey avoidance and
restructuring freight logistics systems;
• system infrastructure and modal choice (NRC, 2009);
• energy intensity — directly related to vehicle and engine design
efficiency, driver behaviour during operation (Davies, 2012), and
usage patterns; and
• fuel carbon intensity — varies for different transport fuels includ-
ing electricity and hydrogen.
Each of these components has good potential for mitigation through
technological developments, behavioural change, or interactions
3
Based on the breakdown into A (total Activity), S (modal Structure), I (modal
energy Intensity), and F (carbon content of Fuels) using the ‘ASIF approach’.
Details of how this decomposition works and the science involved can be found in
Schipper et al. (2000); Kamakaté and Schipper (2009).
between them, such as the deployment of electric vehicles impacting
on average journey distance and urban infrastructure (see Figure 8.2).
Deep long-term emission reductions also require pricing signals and
interactions between the emission factors. Regional differences exist
such as the limited modal choice available in some developing coun-
tries and the varying densities and scales of cities (Banister, 2011a).
Indirect GHG emissions that arise during the construction of transport
infrastructure, manufacture of vehicles, and provision of fuels, are cov-
ered in Chapters 12, 10, and 7 respectively.
8�1�1 The context for transport of passengers
and freight
Around 10 % of the global population account for 80 % of total
motorized passenger-kilometres (p-km) with much of the world’s
population hardly travelling at all. OECD countries dominate GHG
transport emissions (see Figure 8.3) although most recent growth
has taken place in Asia, including passenger kilometres travelled by
low GHG emitting 2- to 3-wheelers that have more than doubled
since 2000 (see Figure 8.4). The link between GDP and transport has
Figure 8�2 | Direct transport GHG emission reductions for each mode and fuel type option decomposed into activity (passenger or freight movements); energy intensity (specific
energy inputs linked with occupancy rate); fuel carbon intensity (including non-CO
2
GHG emissions); and system infrastructure and modal choice. These can be summated for each
modal option into total direct GHG emissions. Notes: p-km = passenger-km; t-km = tonne-km; CNG = compressed natural gas; LPG = liquid petroleum gas (Creutzig etal., 2011;
Bongardt etal., 2013).
Physical
Units
Decomposition
Factors
Examples
Activity
Energy
Intensity
Fuel Carbon
Intensity
Fuels
∑ ∑
Total GHG Emissions =
Modal Shares
tCO
2
eq / MJp-km
mode
/ p-km
total
t-km
mode
/ t-km
total
MJ / p-km
MJ / t-km
p-km
total
t-km
total
Fuel Carbon IntensitySystem-Infrastructure
Modal Choice
Energy Intensity Activity
• Number of Journeys
• Journey Distance
• Journey Avoidance
(Combining Trips, Video
Conferencing, etc.)
… of:
• Diesel
• Gasoline
• CNG / LPG
• Biofuels
• Electricity
• Hydrogen
… of:
• Light Duty Vehicles
(LDVs), 2-/3-Wheelers
• Heavy Duty Vehicles
(HDVs), Buses
• Trains
• Aircraft
• Ships and Boats
• Cycling, Walking
• Occupancy / Loading Rate
• Urban Form
• Transport Infrastructure
(Roads, Rail, Airports, …)
• Behavioural Choice
between Modes
(Speed, Comfort, Cost,
Convenience)
Total GHG Emissions
607607
Transport
8
Chapter 8
been a major reason for increased GHG emissions (Schafer and Vic-
tor, 2000) though the first signs that decoupling may be happening
are now apparent (Newman and Kenworthy, 2011a; Schipper, 2011).
Slower rates of growth, or even reductions in the use of LDVs, have
been observed in some OECD cities (Metz, 2010, 2013; Meyer etal.,
2012; Goodwin and van Dender, 2013; Headicar, 2013) along with a
simultaneous increase in the use of mass transit systems (Kenwor-
thy, 2013). The multiple factors causing this decoupling, and how it
can be facilitated more widely, are not well understood (ITF, 2011;
Goodwin and Van Dender, 2013). However, ‘peak’ travel trends are
not expected to occur in most developing countries in the foreseeable
future, although transport activity levels may eventually plateau at
lower GDP levels than for OECD countries due to higher urban densi-
ties and greater infrastructure constraints (ADB, 2010; Figueroa and
Ribeiro, 2013).
As shown in Figure 8.3, the share of transport emissions tended to
increase due to structural changes as GDP per capita increased, i. e.,
countries became richer. The variance between North America and
other OECD countries (Western Europe and Pacific OECD) shows that
the development path of infrastructure and settlements taken by
developing countries and economies in transition (EITs) will have a sig-
nificant impact on the future share of transport related emissions and,
consequently, total GHG emissions (see Section 12.4).
between them, such as the deployment of electric vehicles impacting
on average journey distance and urban infrastructure (see Figure 8.2).
Deep long-term emission reductions also require pricing signals and
interactions between the emission factors. Regional differences exist
such as the limited modal choice available in some developing coun-
tries and the varying densities and scales of cities (Banister, 2011a).
Indirect GHG emissions that arise during the construction of transport
infrastructure, manufacture of vehicles, and provision of fuels, are cov-
ered in Chapters 12, 10, and 7 respectively.
8�1�1 The context for transport of passengers
and freight
Around 10 % of the global population account for 80 % of total
motorized passenger-kilometres (p-km) with much of the world’s
population hardly travelling at all. OECD countries dominate GHG
transport emissions (see Figure 8.3) although most recent growth
has taken place in Asia, including passenger kilometres travelled by
low GHG emitting 2- to 3-wheelers that have more than doubled
since 2000 (see Figure 8.4). The link between GDP and transport has
Figure 8�2 | Direct transport GHG emission reductions for each mode and fuel type option decomposed into activity (passenger or freight movements); energy intensity (specific
energy inputs linked with occupancy rate); fuel carbon intensity (including non-CO
2
GHG emissions); and system infrastructure and modal choice. These can be summated for each
modal option into total direct GHG emissions. Notes: p-km = passenger-km; t-km = tonne-km; CNG = compressed natural gas; LPG = liquid petroleum gas (Creutzig etal., 2011;
Bongardt etal., 2013).
Physical
Units
Decomposition
Factors
Examples
Activity
Energy
Intensity
Fuel Carbon
Intensity
Fuels
∑ ∑
Total GHG Emissions =
Modal Shares
tCO
2
eq / MJp-km
mode
/ p-km
total
t-km
mode
/ t-km
total
MJ / p-km
MJ / t-km
p-km
total
t-km
total
Fuel Carbon IntensitySystem-Infrastructure
Modal Choice
Energy Intensity Activity
• Number of Journeys
• Journey Distance
• Journey Avoidance
(Combining Trips, Video
Conferencing, etc.)
… of:
• Diesel
• Gasoline
• CNG / LPG
• Biofuels
• Electricity
• Hydrogen
… of:
• Light Duty Vehicles
(LDVs), 2-/3-Wheelers
• Heavy Duty Vehicles
(HDVs), Buses
• Trains
• Aircraft
• Ships and Boats
• Cycling, Walking
• Occupancy / Loading Rate
• Urban Form
• Transport Infrastructure
(Roads, Rail, Airports, …)
• Behavioural Choice
between Modes
(Speed, Comfort, Cost,
Convenience)
Total GHG Emissions
608608
Transport
8
Chapter 8
Figure 8�3 | GHG emissions from transport sub-sectors by regions in 1970, 1990 and 2010 with international shipping and aviation shown separately (IEA, 2012a; JRC / PBL, 2013;
see Annex II.8). Inset shows the relative share of total GHG emissions for transport relative to GDP per capita from 1970 to 2010 for each region and the world. Adapted from
Schäfer etal. (2009), Bongardt etal. (2013) using data from IEA (2012a) and JRC / PBL (2013); see Annex II.8.
*1.71
*2.66
*3.14
*0.07
*0.26
*0.57
*0.14
*0.29
*0.55
*0.26
*0.51
*0.48
*0.14
*0.40
*1.15
*0.48
*0.62
*1.10
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
1970 1990 2010 1970 1990 2010
OECD-1990
1970 1990 2010
ASIA
1970 1990 2010
EIT
1970 1990 2010
MAF
1970 1990 2010
LAM
INT-TRA
GHG Emissions [GtCO
2
eq/yr]
Indirect Emissions
from Electricity Generation
Road
Rail
HFC and Indirect N
2
O
Pipelines etc.
Domestic Waterborne
International and
Coastal Shipping
International Aviation
Domestic Aviation
Total
(Without Indirect Emissions)
*
Transport Sector Share in CO
2
-Emissions [%]
0 5000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000
0
5
10
15
20
25
30
GDP per Capita [Int$
2005
]
East Asia North America Sub Saharan Africa
Economies in Transition South-East Asia and Pacific Western Europe
Latin America and Caribbean Pacific OECD World
Middle East and North Africa South Asia
8�1�2 Energy demands and direct / indirect
emissions
Over 53 % of global primary oil consumption in 2010 was used to
meet 94 % of the total transport energy demand, with biofuels supply-
ing approximately 2 %, electricity 1 %, and natural gas and other fuels
3 % (IEA, 2012b). LDVs consumed around half of total transport
energy (IEA, 2012c). Aviation accounted for 51 % of all international
passenger arrivals in 2011 (UNWTO, 2012) and 17 % of all tourist
travel in 2005 (ICAO, 2007a; UNWTO and UNEP, 2008). This gave 43 %
of all tourism transport CO
2
eq emissions, a share forecast to increase
to over 50 % by 2035 (Pratt et al., 2011). Buses and trains carried
about 34 % of world tourists, private cars around 48 %, and water-
borne craft only a very small portion (Peeters and Dubois, 2010).
Freight transport consumed almost 45 % of total transport energy in
2009 with HDVs using over half of that (Figure 8.5). Ships carried
around 80 % (8.7 Gt) of internationally traded goods in 2011 (UNC-
TAD, 2013) and produced about 2.7 % of global CO
2
emissions
(Buhaug and et. al, 2009).
Direct vehicle CO
2
emissions per kilometre vary widely for each mode
(see Figure 8.6). The particularly wide range of boat types and sizes
gives higher variance for waterborne than for other modes of trans-
port (Walsh and Bows, 2012). Typical variations for freight movement
range from ~2gCO
2
/ t-km for bulk shipping to ~1,700gCO
2
/ t-km for
short-haul aircraft, whereas passenger transport typically ranges from
~20 – 300 gCO
2
/ p-km. GHG emissions arising from the use of liquid
and gaseous fuels produced from unconventional reserves, such as
Figure 8�5 | Final energy consumption of fuels by transport sub-sectors in 2009 for freight and passengers, with heat losses at around two thirds of total fuel energy giving an
average conversion efficiency of fuel to kinetic energy of around 32 %. Note: Width of lines depicts total energy flows. (IEA, 2012d).
Rail
2 EJ
Air
10 EJ
Light
Road
48 EJ
Passenger
53 EJ
Freight
40 EJ
Mechanical
Energy
30 EJ
Losses
63 EJ
Heavy
Road
23 EJ
Water
9 EJ
Heavy Oil,
Biofuels,
Kerosene
20 EJ
Gasoline
39 EJ
Electricity
0.71 EJ
Diesel
32 EJ
Gaseous
0.74 EJ
609609
Transport
8
Chapter 8
from oil sands and shale deposits, vary with the feedstock source and
refining process. Although some uncertainty remains, GHG emissions
from unconventional reserves are generally higher per vehicle kilome-
tre compared with using conventional petroleum products (Brandt,
2009, 2011, 2012; Charpentier etal., 2009; ETSAP, 2010; IEA, 2010a;
Howarth etal., 2011, 2012; Cathles etal., 2012).
‘Sustainable transport’, arising from the concept of sustainable devel-
opment, aims to provide accessibility for all to help meet the basic
daily mobility needs consistent with human and ecosystem health, but
to constrain GHG emissions by, for example, decoupling mobility from
oil dependence and LDV use. Annual transport emissions per capita
correlate strongly with annual income, both within and between coun-
tries (Chapter 5) but can differ widely even for regions with similar
income per capita. For example, the United States has around 2.8 times
the transport emissions per capita than those of Japan (IEA, 2012a).
In least developed countries (LDCs), increased motorized mobility will
produce large increases in GHG emissions but give significant social
benefits such as better access to markets and opportunities to improve
education and health (Africa Union, 2009; Pendakur, 2011; Sietchiping
etal., 2012). Systemic goals for mobility, climate, and energy security
can help develop the more general sustainable transport principles.
Affordable, safe, equitable, and efficient travel services can be pro-
vided with fairness of mobility access across and within generations
(CST, 2002; ECMT, 2004; Bongardt etal., 2011; E C Environment, 2011;
Zegras, 2011; Figueroa and Kahn Ribeiro, 2013).
The following sections of this chapter outline how changes to the
transport sector could reduce direct GHG emissions over the next
decades to help offset the significant global increase in demand pro-
jected for movement of both passengers and freight.
Freight transport consumed almost 45 % of total transport energy in
2009 with HDVs using over half of that (Figure 8.5). Ships carried
around 80 % (8.7 Gt) of internationally traded goods in 2011 (UNC-
TAD, 2013) and produced about 2.7 % of global CO
2
emissions
(Buhaug and et. al, 2009).
Direct vehicle CO
2
emissions per kilometre vary widely for each mode
(see Figure 8.6). The particularly wide range of boat types and sizes
gives higher variance for waterborne than for other modes of trans-
port (Walsh and Bows, 2012). Typical variations for freight movement
range from ~2gCO
2
/ t-km for bulk shipping to ~1,700gCO
2
/ t-km for
short-haul aircraft, whereas passenger transport typically ranges from
~20 – 300 gCO
2
/ p-km. GHG emissions arising from the use of liquid
and gaseous fuels produced from unconventional reserves, such as
Figure 8�5 | Final energy consumption of fuels by transport sub-sectors in 2009 for freight and passengers, with heat losses at around two thirds of total fuel energy giving an
average conversion efficiency of fuel to kinetic energy of around 32 %. Note: Width of lines depicts total energy flows. (IEA, 2012d).
Rail
2 EJ
Air
10 EJ
Light
Road
48 EJ
Passenger
53 EJ
Freight
40 EJ
Mechanical
Energy
30 EJ
Losses
63 EJ
Heavy
Road
23 EJ
Water
9 EJ
Heavy Oil,
Biofuels,
Kerosene
20 EJ
Gasoline
39 EJ
Electricity
0.71 EJ
Diesel
32 EJ
Gaseous
0.74 EJ
Figure 8�4 | Total passenger distance travelled by mode and region in 2000 and 2010
(IEA, 2012c)
Note: Non-motorized modal shares are not included, but can be relatively high in Asia
and Africa. For RC5 region definitions see Annex II.2.
Total Passenger Distance Travelled [Trillion p-km]
0
5
2000
OECD-1990
2010
ASIA
2000 2010 2000
EIT
2010 2000
LAM
2010
MAF
2000 2010
10
15
20
Air
Rail
Buses
Light Duty Vehicles
2-3 Wheelers
610610
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8.2 New developments
in emission trends
and drivers
Assessments of transport GHG emissions require a comprehensive
and differential understanding of trends and drivers that impact on
the movement of goods and people. Transport’s share of total national
GHG emissions range from up to 30 % in high income economies to
less than 3 % in LDCs, mirroring the status of their industry and ser-
vice sectors (Schäfer etal., 2009; Bongardt etal., 2011) (IEA, 2012a;
JRC / PBL, 2013; see Annex II.8) (see inset Figure 8.3). Travel patterns
vary with regional locations and the modes available, and guide the
development of specific emission reduction pathways.
Indicators such as travel activity, vehicle occupancy rates, and fuel
consumption per capita can be used to assess trends towards reduc-
ing emissions and reaching sustainability goals (WBCSD, 2004; Dalk-
mann and Brannigan, 2007; Joumard and Gudmundsson, 2010; Kane,
2010; Litman, 2007; Ramani etal., 2011). For example, petroleum prod-
uct consumption to meet all transport demands in 2009 ranged from
52 GJ / capita in North America to less than 4 GJ / capita in Africa and
India where mobility for many people is limited to walking and cycling.
Likewise, residents and businesses of several cities in the United States
consume over 100GJ / capita each year on transport whereas those in
Figure 8�6 | Typical ranges of direct CO
2
emissions per passenger kilometre and per tonne-kilometre for freight, for the main transport modes when fuelled by fossil fuels including
thermal electricity generation for rail. (ADEME, 2007; US DoT, 2010; Der Boer etal., 2011; NTM, 2012; WBCSD, 2012).
0 25050 150 200100
0 500 1000 1500 2000 2500 3000
Long-haul cargo aircraft
Short-haul cargo aircraft
Long-haul bellyhold in passenger
Short-haul bellyhold in passenger
Passenger aircraft
Bulk tanker - ocean
Bulk carrier - ocean
Container ship - ocean
Container ship - coastal
Roll-on, roll-off ferry
Barge
Passenger ferry
Electric freight train
Diesel freight train
Passenger rail, metro, tram
HDV large
HDV medium
HDV small
LDV commercial (van)
2- and 3-wheel motorbike
Coach, bus, rapid transit
LDV Taxi gasoline, diesel, hybrid
LDV gasoline, diesel, hybrid
Road
Rail
Waterborne
Air
Freight [g CO
2
/t-km]
Passenger [g CO
2
/p-km]
Direct* CO
2
Emissions per Distance [gCO
2
/km] Direct* CO
2
Emissions per Distance [gCO
2
/km]
*The ranges only give an indication of direct vehicle fuel emissions. They exclude indirect emissions arising from
vehicle manufacture, infrastructure, etc. included in life-cycle analyses except from electricity used for rail.
611611
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many Indian and Chinese cities use less than 2 GJ / capita (Newman and
Kenworthy, 2011a). For freight, companies are starting to adopt green
initiatives as a means of cost savings and sustainability initiatives (Fürst
and Oberhofer, 2012). Such programmes are also likely to reduce GHG
emissions, although the long-term impact is difficult to assess.
8�2�1 Trends
As economies have shifted from agriculture to industry to service, the
absolute GHG emissions from transport (Figure 8.1) and the share
of total GHG emissions by the transport sector (Chapter 5.2.1) have
risen considerably. Total LDV ownership is expected to double in the
next few decades (IEA, 2009) from the current level of around 1 bil-
lion vehicles (Sousanis, 2011). Two-thirds of this growth is expected
in non-OECD countries where increased demand for mobility is also
being met by motorized two-wheelers and expansion of bus and rail
public transport systems. However, passenger kilometres travelled and
per capita ownership of LDVs will likely remain much lower than in
OECD countries (Cuenot etal., 2012; Figueroa etal., 2013).
Air transport demand is projected to continue to increase in most
OECD countries (see Section 8.9). Investments in high-speed rail sys-
tems could moderate growth rates over short- to medium-haul dis-
tances in Europe, Japan, China, and elsewhere (Park and Ha, 2006;
Gilbert and Perl, 2010; Åkerman, 2011; Salter etal., 2011).
There is limited evidence that reductions to date in carbon intensity,
energy intensity, and activity, as demonstrated in China, Japan, and
Europe, have adequately constrained transport GHG emissions growth in
the context of mitigation targets. Recent trends suggest that economic,
lifestyle, and cultural changes will be insufficient to mitigate global
increases in transport emissions without stringent policy instruments,
incentives, or other interventions being needed (see Section 8.10).
8�2�1�1 Non-CO
2
greenhouse gas emissions, black
carbon, and aerosols
The transport sector emits non-CO
2
pollutants that are also climate
forcers. These include methane, volatile organic compounds (VOCs),
nitrogen oxides (NO
x
), sulphur dioxide (SO
2
), carbon monoxide (CO),
F-gases, black carbon, and non-absorbing aerosols (Ubbels etal., 2002;
Sections 5.2.2 and 6.6.2.1). Methane emissions are largely associ-
ated with leakage from the production of natural gas and the filling
of compressed natural gas vehicles; VOCs, NO
x
and CO are emitted by
internal combustion engines; and F-gas emissions generally from air
conditioners (including those in vehicles) and refrigerators. Contrails
from aircraft and emissions from ships also impact on the troposphere
and the marine boundary layer, respectively (Fuglestvedt etal., 2009;
Lee etal., 2010). Aviation emissions can also impact on cloud forma-
tion and therefore have an indirect effect on climate forcing (Burkhardt
and Kärcher, 2011).
Black carbon and non-absorbing aerosols, emitted mainly during diesel
engine operation, have short lifetimes in the atmosphere of only days
to weeks, but can have significant direct and indirect radiative forc-
ing effects and large regional impacts (Boucher etal., 2013). In North
and South America and Europe, over half the black carbon emissions
result from combusting diesel and other heavy distillate fuels (includ-
ing marine oil), in vehicle engines (Bond et al., 2013). Black carbon
emissions are also significant in parts of Asia, Africa, and elsewhere
from biomass and coal combustion, but the relative contribution from
transport is expected to grow in the future. There is strong evidence
that reducing black carbon emissions from HDVs, off-road vehicles, and
ships could provide an important short term strategy to mitigate atmo-
spheric concentrations of positive radiative forcing pollutants (USEPA,
2012; Shindell etal., 2013; Chapter 6.6; WG I Chapter 7).
Conversely, transport is also a significant emitter of primary aerosols
that scatter light and gases that undergo chemical reactions to pro-
duce secondary aerosols. Primary and secondary organic aerosols, sec-
ondary sulphate aerosols formed from sulphur dioxide emissions, and
secondary nitrate aerosols from nitrogen oxide emissions from ships,
aircraft, and road vehicles, can have strong, local, and regional cooling
impacts (Boucher etal., 2013).
The relative contributions of different short-term pollutants to radiative
forcing in 2020 have been equated by Unger etal. (2010) to having
continuous constant GHG emissions since 2000. Although this study
did not provide a projection for future emissions scenarios, it did offer
a qualitative comparison of short- and long-term impacts of different
pollutants. Relative to CO
2
, major short-term impacts stem from black
carbon, indirect effects of aerosols and ozone from land vehicles, and
aerosols and methane emissions associated with ships and aircraft.
Their relative impacts due to the longer atmospheric lifetime of CO
2
will be greatly reduced when integrated from the present time to 2100.
Although emissions of non-CO
2
GHGs and aerosols can be mitigated
by reducing carbon intensity, improving energy intensity, changing to
lower-carbon modes, and reducing transport activity, they can also
be significantly reduced by technologies that prevent their formation
or lead to their destruction using after-treatments. Emission control
devices such as diesel particulate filters and selective catalytic reduc-
tion have fuel efficiency penalties that can lead to an increase in trans-
port CO
2
emissions.
Non-CO
2
emissions from road transport and aviation and shipping
activities in ports have historically been constrained by local air qual-
ity regulations that are directed at near-surface pollution and seek to
protect human health and welfare by reducing ozone, particulate mat-
ter, sulphur dioxide, and toxic components or aerosols, including vana-
dium, nickel, and polycyclic aromatic hydrocarbons (Verma etal. 2011).
The importance of regional climate change in the context of mitiga-
tion has prompted a growing awareness of the climate impact of these
emissions. Policies are already in place for reducing emissions of
F-gases, which are expected to continue to decrease with time (Prinn
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etal., 2000). More efforts are being directed at potential programmes
to accelerate control measures to reduce emissions of black carbon,
ozone precursors, aerosols, and aerosol precursors (Lin and Lin, 2006).
Emissions from road vehicles continue to decrease per unit of travel
in many regions due to efforts made to protect human health from
air pollution. The implementation of these controls could potentially
be accelerated as a driver to mitigate climate change (Oxley et al.,
2012). Short-term mitigation strategies that focus on black carbon and
contrails from aircraft, together with national and international pro-
grammes to reduce aerosol and sulphate emissions from shipping, are
being implemented (Buhaug and et. al, 2009; Lack, 2012). However,
the human health benefits from GHG emissions reductions and the co-
benefits of climate change mitigation through black carbon reductions
need to be better assessed (Woodcock etal., 2009).
8�2�2 Drivers
The major drivers that affect transport trends are travel time budgets,
costs and prices, increased personal income, and social and cultural
factors (Schäfer, 2011). For a detailed discussion of effects of urban
form and structure on elasticities of vehicle kilometres travelled see
Section 12.4.2.
Travel time budget� Transport helps determine the economy of a city
or region based on the time taken to move people and goods around.
Travel time budgets are usually fixed and tied to both travel costs and
time costs (Noland, 2001; Cervero, 2001; Noland and Lem, 2002).
Because cities vary in the proportion of people using different trans-
port modes, urban planners tend to try to adapt land use planning to
fit these modes in order to enable speeds of around 5 km / hr for walk-
ing, 20 – 30 km / hr for mass transit, and 40 – 50 km / hr for LDVs, though
subject to great variability. Infrastructure and urban areas are usually
planned for walking, mass transit, or LDVs so that destinations can be
reached in half an hour on average (Newman and Kenworthy, 1999).
Urban travel time budgets for a typical commute between work and
home average around 1.1 – 1.3 hours per traveller per day in both
developed and developing economies (Zahavi and Talvitie, 1980; van
Wee etal., 2006). Higher residential density can save fuel for LDVs, but
leads to more congested commutes (Small and Verhoef, 2007; Downs,
2004). While new road construction can reduce LDV travel time in the
short run, it also encourages increased LDV demand, which typically
leads to increases in travel time to a similar level as before (Maat and
Arentze, 2012). Moreover, land uses quickly adapt to any new road
transport infrastructure so that a similar travel time eventually resumes
(Mokhtarian and Chen, 2004).
Regional freight movements do not have the same fixed time demands,
but rather are based more on the need to remain competitive by limit-
ing transport costs to a small proportion of the total costs of the goods
(Schiller etal. 2010). See also Section 12.4.2.4 on accessibility aspects
of urban form.
Costs and prices� The relative decline of transport costs as a share of
increasing personal expenditure has been the major driver of increased
transport demand in OECD countries throughout the last century and
more recently in non-OECD countries (Mulalic etal., 2013). The price of
fuel, together with the development of mass transit systems and non-
motorized transport infrastructure, are major factors in determining the
level of LDV use versus choosing public transport, cycling, or walking
(Hughes etal., 2006). Transport fuel prices, heavily influenced by taxes,
also impact on the competition between road and rail freight. The costs
of operating HDVs, aircraft, and boats increase dramatically when fuel
costs go up given that fuel costs are a relatively high share of total costs
(Dinwoodie, 2006). This has promulgated the designs of more fuel effi-
cient engines and vehicle designs (Section 8.3) (IEA, 2009). Although the
average life of aircraft and marine engines is two to three decades and
fleet turnover is slower than for road vehicles and small boats, improv-
ing their fuel efficiency still makes good economic sense (IEA, 2009).
The high cost of developing new infrastructure requires significant cap-
ital investment that, together with urban planning, can be managed
and used as a tool to reduce transport demand and also encourage
modal shift (Waddell etal., 2007). Changing urban form through plan-
ning and development can therefore play a significant role in the miti-
gation of transport GHG emissions (see Section 8.4) (Kennedy etal.,
2009). See also Section 12.5.2 on urban policy instruments.
Social and cultural factors. Population growth and changes in
demographics are major drivers for increased transport demand. Eco-
nomic structural change, particularly in non-OECD countries, can lead
to increased specialization of jobs and a more gender-diversified work-
force, which can result in more and longer commutes (McQuaid and
Chen, 2012). At the household level, once a motorized vehicle becomes
affordable, even in relatively poor households, then it becomes a major
item of expenditure; however, ownership has still proven to be increas-
ingly popular with each new generation (Giuliano and Dargay, 2006;
Lescaroux, 2010; Zhu etal., 2012). Thus, there is a high growth rate
in ownership of motorized two-wheel vehicles and LDVs evident in
developing countries, resulting in increasing safety risks for pedestrians
and non-motorized modes (Nantulya and Reich 2002; Pendakur, 2011).
The development of large shopping centres and malls usually located
outside the city centre allows many products to be purchased by a con-
sumer following a single journey but the travel distance to these large
shopping complexes has tended to increase (Weltevreden, 2007). For
freight transport, economic globalization has increased the volume and
distance of movement of goods and materials (Henstra etal., 2007).
Modal choice can be driven by social factors that are above and
beyond the usual time, cost, and price drivers. For example, some
urban dwellers avoid using mass transit or walking due to safety and
security issues. However, there is evidence that over the past decade
younger people in some OECD cities are choosing walking, cycling, and
mass transit over LDVs (Parkany etal., 2004; Newman and Kenworthy,
2011b; Delbosc and Currie, 2013; Kuhnimhof etal., 2013) although this
trend could change as people age (Goodwin and van Dender, 2013).
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Another example is that in some societies, owning and driving a LDV
can provide a symbolic function of status and a basis for sociability
and networking through various sign-values such as speed, safety, suc-
cess, career achievement, freedom, masculinity, and emancipation of
women (Mokhtarian and Salomon, 2001; Steg, 2005; Bamberg etal.,
2011; Carrabine and Longhurst, 2002; Miller, 2001; Sheller, 2004; Urry,
2007). In such cases, the feeling of power and superiority associated
with owning and using a LDV may influence driver behaviour, for
example, speeding without a concern for safety, or without a concern
about fuel consumption, noise, or emissions (Brozović and Ando, 2009;
Tiwari and Jain, 2012). The possible effects on travel patterns from
declining incomes are unclear.
Lifestyle and behavioural factors are important for any assessment
of potential change to low-carbon transport options and additional
research is needed to assess the willingness of people to change
(Ashton-Graham, 2008; Ashton-Graham and Newman, 2013). Disrup-
tive technologies such as driverless cars and consumer-based manu-
facturing (e. g. 3-D printing) could impact on future transport demands
but these are difficult to predict. Likewise, the impact of new informa-
tion technology (IT) applications and telecommuting could potentially
change travel patterns, reduce trips, or facilitate interactions with the
mode of choice (ITF, 2011). Conversely, increased demand for tourism
is expected to continue to be a driver for all transport modes (Sections
8.1 and 10.4; Gössling etal., 2009).
8.3 Mitigation technology
options, practices and
behavioural aspects
Technological improvements and new technology-related practices
can make substantial contributions to climate change mitigation in
the transport sector. This section focuses on energy intensity reduction
technology options for LDVs, HDVs, ships, trains and aircraft and fuel
carbon intensity reduction options related to the use of natural gas,
electricity, hydrogen and biofuels. It also addresses some technology-
related behavioural aspects concerning the uptake and use of new
technologies, behaviour of firms, and rebound effects. Urban form and
modal shift options are discussed in Section 8.4.
8�3�1 Energy intensity reduction — incremental
vehicle technologies
Recent advances in LDVs in response to strong regulatory efforts in
Japan, Europe, and the United States have demonstrated that there is
substantial potential for improving internal combustion engines (ICEs)
with both conventional and hybrid drive-trains. Recent estimates sug-
gest substantial additional, unrealized potentials exist compared to
similar-sized, typical 2007 – 2010 vehicles, with up to 50 % improve-
ments in vehicle fuel economy (in MJ / km or litres / 100km units, or
equal to 100 % when measured as km / MJ, km / l, or miles per gal-
lon) (Bandivadekar etal., 2008; Greene and Plotkin, 2011). Similar or
slightly lower potentials exist for HDVs, waterborne craft, and aircraft.
8�3�1�1 Light duty vehicles
As of 2011, leading-edge LDVs had drive-trains with direct injection
gasoline or diesel engines (many with turbochargers), coupled with
automated manual or automatic transmissions with six or more gears
(SAE International, 2011). Drive-train redesigns of average vehicles to
bring them up to similar levels could yield reductions in fuel consump-
tion and GHG emissions of 25 % or more (NRC, 2013). In European
Union 27 (EU27), the average tested emissions of 2011 model LDVs
was 136 gCO
2
/ km, with some models achieving below 100 gCO
2
/ km
(EEA, 2012). In developing countries, vehicle technology levels are typi-
cally lower, although average fuel economy can be similar since vehicle
size, weight, and power levels are also typically lower (IEA, 2012d).
Hybrid drive-trains (ICE plus electric motor with battery storage) can
provide reductions up to 35 % compared to similar non-hybridized
vehicles (IEA, 2012e) and have become mainstream in many countries,
but with only a small share of annual sales over the last decade except
in Japan, where over two million had been sold by 2012 (IEA, 2012e).
There is substantial potential for further advances in drive-train design
and operation, and for incremental technologies (NRC, 2013). There is
often a time lag between when new technologies first appear in OECD
countries and when they reach developing countries, which import
mostly second-hand vehicles (IEA, 2009).
Lower fuel consumption can be achieved by reducing the loads that
the engine must overcome, such as aerodynamic forces, auxiliary com-
ponents (including lighting and air conditioners), and rolling resis-
tance. Changes that reduce energy loads include improved aerodynam-
ics, more efficient auxiliaries, lower rolling-resistance tyres, and weight
reduction. With vehicle performance held constant, reducing vehicle
weight by 10 % gives a fuel economy improvement of about 7 % (EEA,
2006). Together, these non-drive-train changes offer potential fuel
consumption reductions of around 25 % (ICCT, 2012a; NRC, 2013).
Combined with improved engines and drive-train systems, overall LDV
fuel consumption for new ICE-powered vehicles could be reduced by
at least half by 2035 compared to 2005 (Bandivadekar etal., 2008;
NRC, 2013). This predicted reduction is consistent with the Global Fuel
Economy Initiative target for new LDVs of a 50 % reduction in average
fuel use per kilometre in 2030 compared to 2005 (Eads, 2010).
8�3�1�2 Heavy-duty vehicles
Most modern medium and HDVs already have efficient diesel engines
(up to 45 % thermal efficiency), and long-haul trucks often have
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streamlined spoilers on their cabs to reduce drag, particularly in OECD
countries. Aerodynamic drag can also be reduced using other modifica-
tions offering up to 10 % reduction in fuel consumption (TIAX, 2009;
NRC, 2010; AEA, 2011). In non-OECD countries, many older trucks with
relatively inefficient (and highly polluting) engines are common. Truck
modernization, along with better engine, tyre, and vehicle maintenance,
can significantly improve fuel economy in many cases.
Medium and HDVs in the United States can achieve a reduction in
energy intensity of 30 – 50 % by 2020 by using a range of technology
and operational improvements (NRC, 2010a). Few similar estimates
are available in non-OECD countries, but most technologies eventually
will be applicable for HDVs around the world.
Expanding the carrying capacity of HDVs in terms of both volume and
weight can yield significant net reductions in the energy intensity of
trucks so long as the additional capacity is well utilized. A comparison
of the performance of 18 longer and heavier HDVs in nine countries
(ITF / OECD, 2010) concluded that higher capacity vehicles can signifi-
cantly reduce CO
2
emissions per t-km. The use of long combination
vehicles rather than single trailer vehicles has been shown to cut direct
GHG emissions by up to 32 % (Woodrooffe and Ash, 2001).
Trucks and buses that operate largely in urban areas with a lot of
stop-and-go travel can achieve substantial benefits from using electric
hybrid or hydraulic hybrid drive-trains. Typically a 20 – 30 % reduction
in fuel consumption can be achieved via hybridization (Chandler etal.,
2006; AEA, 2011).
8�3�1�3 Rail, waterborne craft, and aircraft
Rail is generally energy efficient, but improvements can be gained from
multiple drive-trains and load-reduction measures. For example, the high-
speed ‘Shinkansen’ train in Japan gained a 40 % reduction of energy
consumption by optimizing the length and shape of the lead nose, reduc-
ing weight, and by using efficient power electronics (UIC, 2011); Amtrack
in the United States employed regenerative braking systems to reduce
energy consumption by 8 % (UIC, 2011); and in China, electrification and
other measures from 1975 to 2007 contributed to a 87 % reduction in
CO
2
emission intensity of the rail system (He etal., 2010).
Shipping is a comparatively efficient mode of freight and passenger
transport, although size and load factor are important determinants
for specific motorized craft, large and small. Efficiency of new-built ves-
sels can be improved by 5 – 30 % through changes in engine and trans-
mission technologies, waste heat recovery, auxiliary power systems,
propeller and rotor systems, aerodynamics and hydrodynamics of the
hull structure, air lubrication systems, electronically controlled engine
systems to give fuel efficient speeds, and weight reduction (IMO, 2009;
Notteboom and Vernimmen, 2009; AEA, 2007; IEA, 2009; IMO, 2009;
ICCT, 2011). Retrofit and maintenance measures can provide additional
efficiency gains of 4 – 20 % (Buhaug and et. al, 2009) and operational
changes, such as anti-fouling coatings to cut water resistance, along
with operation at optimal speeds, can provide 5 – 30 % improvement
(Pianoforte, 2008; Corbett etal., 2009; WSC, 2011).
Several methods for improving waterborne craft efficiency are already
in use. For example, wind propulsion systems such as kites and para-
foils can provide lift and propulsion to reduce fuel consumption by up
to 30 %, though average savings may be much less (Kleiner, 2007).
Photovoltaics and small wind turbines can provide on-board electricity
and be part of ‘cold ironing’ electric systems in ports. For international
shipping, combined technical and operational measures have been
estimated to potentially reduce energy use and CO
2
emissions by up
to 43 % per t-km between 2007 and 2020 and by up to 60 % by 2050
(Crist, 2009; IMO, 2009).
Aircraft designs have received substantial, on-going technology effi-
ciency improvements over past decades (ITF, 2009) typically offering
a 20 – 30 % reduction in energy intensity compared to older aircraft
models (IEA, 2009). Further fuel efficiency gains of 40 – 50 % in the
2030 – 2050 timeframe (compared to 2005) could come from weight
reduction, aerodynamic and engine performance improvements, and
aircraft systems design (IEA, 2009). However, the rate of introduction
of major aircraft design concepts could be slow without significant
policy incentives, regulations at the regional or global level, or fur-
ther increases in fuel prices (Lee, 2010). Retrofit opportunities, such as
engine replacement and adding ‘winglets’, can also provide significant
reductions (Gohardani etal., 2011; Marks, 2009). Improving air traffic
management can reduce CO
2
emissions through more direct routings
and flying at optimum altitudes and speeds (Dell’Olmo and Lulli, 2003;
Pyrialakou et al., 2012). Efficiency improvements of ground service
equipment and electric auxiliary power units can provide some addi-
tional GHG reductions (Pyrialakou etal., 2012).
8�3�2 Energy intensity reduction — advanced
propulsion systems
At present, most vehicles and equipment across all transport modes are
powered by ICEs, with gasoline and diesel as the main fuels for LDVs;
gasoline for 2- and 3-wheelers and small water craft; diesel for HDVs;
diesel or heavy fuel oil for ships and trains (other than those using grid
electricity); and kerosene for aircraft turbine engines. New propulsion
systems include electric motors powered by batteries or fuel cells, tur-
bines (particularly for rail), and various hybridized concepts. All offer
significant potential reductions in GHG, but will require considerable
time to penetrate the vehicle fleet due to slow stock turnover rates.
8�3�2�1 Road vehicles — battery and fuel cell electric-
drives
Battery electric vehicles (BEVs) emit no tailpipe emissions and have
potentially very low fuel-production emissions (when using low-car-
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bon electricity generation) (Kromer and Heywood, 2007). BEVs oper-
ate at a drive-train efficiency of around 80 % compared with about
20 – 35 % for conventional ICE LDVs. At present, commercially avail-
able BEVs typically have a limited driving range of about 100 – 160km,
long recharge times of four hours or more (except with fast-charging
or battery switching systems), and high battery costs that lead to rel-
atively high vehicle retail prices (Greene and Plotkin, 2011). Lithium
ion (Li-ion) batteries will likely improve but new battery technologies
(e. g., Li-air, Li-metal, Li-sulphur) and ultra-capacitors may be required
to achieve much higher energy and power densities (IEA, 2009; NRC,
2013). Compressed air as an energy storage medium for LDVs is
thermo-dynamically inefficient and would require high storage volume
(Creutzig etal., 2009).
Plug-in hybrid electric vehicles (PHEVs) capable of grid recharging
typically can operate on battery electricity for 20 to 50 km, but emit
CO
2
when their ICE is operating. The electric range of PHEVs is heav-
ily dependent on the size of battery, design architectures, and control
strategies for the operation of each mode (Plotkin etal., 2001).
For HDVs, the use of BEVs is most applicable to light-medium duty
urban vehicles such as delivery vans or garbage collection trucks
whose drive cycles involve frequent stops and starts and do not need a
long range (TIAX, 2009; AEA, 2011). Transit buses are also good candi-
dates for electrification either with batteries or more commonly using
overhead wire systems (IEA, 2009). Electric 2-wheelers with lower
requirements for battery and motor capacities are a mature technology
with widespread acceptance, especially in developing countries (Wein-
ert, 2008). For example, there were over 120 million electric 2-wheel-
ers in China by the end of 2010 (Wu etal., 2011).
Fuel cell vehicles (FCVs) can be configured with conventional, hybrid,
or plug-in hybrid drive-trains. The fuel cells generate electricity from
hydrogen that may be generated on-board (by reforming natural gas,
methanol, ammonia, or other hydrogen-containing fuel), or produced
externally and stored on-board after refuelling. FCVs produce no tail-
pipe emissions except water and can offer a driving range similar to
today’s gasoline / diesel LDVs, but with a high cost increment. Fuel cells
typically operate with a conversion efficiency of 54 – 61 % (significantly
better than ICEs can achieve), giving an overall fuel-cycle efficiency of
about 35 – 49 % for an LDV (JHFC, 2011).
Although a number of FCV LDVs, HDVs, and buses have been dem-
onstrated and some are expected to become commercially available
within five years, overall it could take 10 years or longer for FCVs to
achieve commercial success based on current oil and vehicle purchase
prices (IEA, 2012e).
8�3�2�2 Rail, waterborne craft, and aircraft
Diesel-hybrid locomotives demonstrated in the UK and advanced types
of hybrid drive-trains under development in the United States and
Japan, could save 10 – 20 % of diesel fuel plus around a 60 % reduc-
tion of NO
x
and particulate matter compared to conventional locomo-
tives (JR East, 2011). A shift to full electrification may enable many
rail systems to reach very low CO
2
emissions per kilometre where elec-
tricity generation has been deeply decarbonized. Fuel cell systems for
rail may be attractive in areas lacking existing electricity infrastructure
(IEA, 2012e).
Most ocean-going ships will probably continue to use marine diesel
engines for the foreseeable future, given their high reliability and low
cost. However, new propulsion systems are in development. Full elec-
trification appears unlikely given the energy storage requirements for
long-range operations, although on-board solar power generation sys-
tems could be used to provide auxiliary power and is already used for
small craft (Crist, 2009). Fuel cell systems (commonly solid-oxide) with
electric motors could be used for propulsion, either with hydrogen fuel
directly loaded and stored on board or with on-board reforming. How-
ever, the cost of such systems appears relatively high, as are nuclear
power systems as used in some navy vessels.
For large commercial aircraft, no serious alternative to jet engines for
propulsion has been identified, though fuel-switching options are pos-
sible, including ‘drop-in’ biofuels (that are fungible with petroleum
products, can be blended from 0 to 100 %, and are compatible with all
existing engines) or hydrogen. Hydrogen aircraft are considered only
a very long run option due to hydrogen’s low energy density and the
difficulty of storing it on board, which requires completely new aircraft
designs and likely significant compromises in performance (Cryoplane,
2003). For small, light aircraft, advanced battery electric / motor sys-
tems could be deployed but would have limited range (Luongo etal.,
2009).
8�3�3 Fuel carbon intensity reduction
In principle, low-carbon fuels from natural gas, electricity, hydrogen,
and biofuels (including biomethane) could all enable transport systems
to be operated with low direct fuel-cycle CO
2
eq emissions, but this
would depend heavily on their feedstocks and conversion processes.
Natural gas (primarily methane) can be compressed (CNG) to replace
gasoline in Otto-cycle (spark ignition) vehicle engines after minor mod-
ifications to fuel and control systems. CNG can also be used to replace
diesel in compression ignition engines but significant modifications are
needed. Denser storage can be achieved by liquefaction of natural gas
(LNG), which is successfully being used for long-haul HDVs and ships
(Buhaug and et. al, 2009; Arteconi etal., 2010). The energy efficiency
of driving on CNG is typically similar to that for gasoline or diesel but
with a reduction of up to 25 % in tailpipe emissions (CO
2
/ km) because
of differences in fuel carbon intensity. Lifecycle GHG analysis suggests
lower net reductions, in the range of 10 – 15 % for natural gas fuel sys-
tems. They may also provide a bridge to lower carbon biomethane sys-
tems from biogas (IEA, 2009).
616616
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Electricity can be supplied to BEVs and PHEVS via home or public
rechargers. The varying GHG emissions intensity of power grids directly
affects lifecycle CO
2
eq emissions (IEA, 2012e). Since the GHG inten-
sity of a typical coal-based power plant is about 1000 gCO
2
eq / kWh
at the outlet (Wang, 2012a), for a BEV with efficiency of 200 Wh / km,
this would equate to about 200 gCO
2
eq / km, which is higher than for
an efficient ICE or hybrid LDV. Using electricity generated from nuclear
or renewable energy power plants, or from fossil fuel plants with car-
bon dioxide capture and storage (CCS), near-zero fuel-cycle emissions
could result for BEVs. The numbers of EVs in any country are unlikely to
reach levels that significantly affect national electricity demand for at
least one to two decades, during which time electricity systems could
be at least partially decarbonized and modified to accommodate many
EVs (IEA, 2012e).
Hydrogen used in FCVs, or directly in modified ICEs, can be produced
by the reforming of biomass, coal or natural gas (steam methane
reforming is well-established in commercial plants); via commercial
but relatively expensive electrolysis using electricity from a range of
sources including renewable; or from biological processes (IEA, 2009).
The mix of feedstocks largely determines the well-to-wheel GHG emis-
sions of FCVs. Advanced, high-temperature and photo-electrochemical
technologies at the R&D stage could eventually become viable path-
ways (Arvizu etal., 2011). Deployment of FCVs (8.3.2.1) needs to be
accompanied by large, geographically focused, investments into hydro-
gen production and distribution and vehicle refuelling infrastructure.
Costs can be reduced by strategic placement of stations (Ogden and
Nicholas, 2011) starting with specific locations (‘lighthouse cities’) and
a high degree of coordination between fuel suppliers, vehicle manu-
facturers and policy makers is needed to overcome ‘chicken-or-egg’
vehicle / fuel supply problems (ITS-UC Davis, 2011).
A variety of liquid and gaseous biofuels can be produced from various
biomass feedstocks using a range of conversion pathways (Chapter
11.A.3). The ability to produce and integrate large volumes of biofu-
els cost-effectively and sustainably are primary concerns of which
policy makers should be aware (Sims etal., 2011). In contrast to elec-
tricity and hydrogen, liquid biofuels are relatively energy-dense and
are, at least in certain forms and blend quantities, compatible with
the existing petroleum fuel infrastructure and with all types of ICEs
installed in LDVs, HDVs, waterborne craft, and aircraft. Ethanol and
biodiesel (fatty-acid-methyl-ester, FAME) can be blended at low levels
(10 – 15 %) with petroleum fuels for use in unmodified ICEs. New ICEs
can be cheaply modified during manufacture to accommodate much
higher blends as exemplified by ‘flex-fuel’ gasoline engines where
ethanol can reach 85 % of the fuel blend (ANFAVEA, 2012). However,
ethanol has about a 35 % lower energy density than gasoline, which
reduces vehicle range — particularly at high blend levels — that can be
a problem especially for aircraft. Synthetic ‘drop-in’ biofuels have simi-
lar properties to diesel and kerosene fuels. They can be derived from a
number of possible feedstocks and conversion processes, such as the
hydro-treatment of vegetable oils or the Fischer-Tropsch conversion of
biomass (Shah, 2013). Bio-jet fuels suitable for aircraft have been dem-
onstrated to meet the very strict fuel specifications required (Takeshita
and Yamaji, 2008; Caldecott and Tooze, 2009). Technologies to produce
ligno-cellulosic, Fisher-Tropsch, algae-based, and other advanced bio-
fuels are in development, but may need another decade or more to
achieve widespread commercial use (IEA, 2011a). Bio-methane from
suitably purified biogas or landfill gas can also be used in natural gas
vehicles (REN21, 2012).
Biofuels have direct, fuel-cycle GHG emissions that are typically
30 – 90 % lower per kilometre travelled than those for gasoline or diesel
fuels. However, since for some biofuels, indirect emissions — including
from land use change — can lead to greater total emissions than when
using petroleum products, policy support needs to be considered on a
case by case basis (see Chapter 11.13 and, for example, Lapola etal.,
2010; Plevin etal., 2010; Wang etal., 2011; Creutzig etal., 2012a).
8�3�4 Comparative analysis
The vehicle and power-train technologies described above for reducing
fuel consumption and related CO
2
emissions span a wide range and
are not necessarily additive. When combined, and including different
propulsion and fuel systems, their overall mitigation potential can be
evaluated as an integrated fuel / vehicle system (see Section 8.6). How-
ever, to produce an overall mitigation evaluation of the optimal design
of a transport system, non-CO
2
emissions, passenger or freight occu-
pancy factors, and indirect GHG emissions from vehicle manufacture
and infrastructure should also be integrated to gain a full comparison
of the relative GHG emissions across modes (see Section 8.4; Hawkins
etal., 2012; Borken-Kleefeld etal., 2013).
Taking LDVs as an example, a comparative assessment of current and
future fuel consumption reduction potentials per kilometre has been
made (Figure 8.7), starting from a 2010 baseline gasoline vehicle at
about 8 lge
4
/ 100km and 195 g / km CO
2
. Using a range of technologies,
average new LDV fuel economy can be doubled (in units of distance
per energy, i. e., energy intensity cut by 50 %). Further improvements
can be expected for hybrids, PHEVs, BEVs, and FCVs, but several hur-
dles must be overcome to achieve wide market penetration (see Sec-
tion 8.8). Vehicle cost increases due to new technologies could affect
customers’ willingness to pay, and thus affect market penetration,
although cost increases would be at least partly offset by fuel cost sav-
ings (see Section 8.6).
8�3�5 Behavioural aspects
The successful uptake of more efficient vehicles, advanced technolo-
gies, new fuels, and the use of these fuels and vehicles in ‘real life’
conditions, involves behavioural aspects.
4
“Litre per gasoline equivalent” allows for a comparison between fuels with differ-
ent energy contents.
Figure 8�7 | Indicative fuel consumption reduction potential ranges for a number of
LDV technology drive-train and fuel options in 2010 and 2030, compared with a base-
line gasoline internal combustion engine (ICE) vehicle consuming 8 l / 100km in 2010.
(Based on Kobayashi etal., 2009; Plotkin etal., 2009; IEA, 2012b; NRC, 2013).
0%
0 20 40
8060
100
FCEV
BEV
Gasoline PHEV
Gasoline Hybrid
Diesel ICE
Gasoline ICE
FCEV
BEV
Gasoline PHEV
Gasoline Hybrid
Diesel ICE
Gasoline ICE
Change in Energy Use per Vehicle km [%]
2010
2030
617617
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Chapter 8
• Purchase behaviour: Few consumers attempt to minimize the
lifecycle costs of vehicle ownership (Greene, 2010a), which leads
to a considerable imbalance of individual costs versus society-wide
benefits. There is often a lack of interest in purchasing more fuel
efficient vehicles (Wozny and Allcott, 2010) due to imperfect infor-
mation, information overload in decision making, and consumer
uncertainty about future fuel prices and vehicle life (Anderson
etal., 2011; Small, 2012). This suggests that in order to promote
the most efficient vehicles, strong policies such as fuel economy
standards, sliding-scale vehicle tax systems, or ‘feebate’ systems
with a variable tax based on fuel economy or CO
2
emissions may
be needed (Section 8.10) (Gallagher and Muehlegger, 2011). Vehi-
cle characteristics are largely determined by the desires of new-car
buyers in wealthier countries, so there may be a five-year or longer
lag before new technologies reach second-hand vehicle markets in
large quantities, particularly through imports to many developing
countries (though this situation will likely change in the coming
decades as new car sales rise across non-OECD countries) (IEA,
2009).
• New technologies / fuels: Consumers’ unwillingness to purchase
new types of vehicles with significantly different attributes (such
as smaller size, shorter range, longer refuelling or recharging time,
higher cost) is a potential barrier to introducing innovative pro-
pulsion systems and fuels (Brozović and Ando, 2009). This may
relate simply to the perceived quality of various attributes or to
risk aversion from uncertainty (such as driving range anxiety for
BEVs
5
) (Wenzel and Ross, 2005). The extent to which policies must
compensate by providing incentives varies but may be substantial
(Gallagher and Muehlegger, 2011).
• On-road fuel economy: The fuel economy of a vehicle as quoted
from independent testing can be up to 30 % better than that actu-
ally achieved by an average driver on the road (IEA, 2009; TMO,
2010; ICCT, 2012). This gap reflects a combination of factors
including inadequacies in the test procedure, real-world driving
conditions (e. g., road surface quality, weather conditions), driver
behaviour, and vehicle age and maintenance. Also congested traf-
fic conditions in OECD cities differ from mixed-mode conditions in
some developing countries (Tiwari etal., 2008; Gowri etal., 2009).
Some countries have attempted to adjust for these differences in
their public vehicle fuel economy information. A significant reduc-
tion in the gap may be achievable by an ‘integrated approach’ that
includes better traffic management, intelligent transport systems,
and improved vehicle and road maintenance (IEA, 2012e).
• Eco-Driving: A 5 – 10 % improvement in on-road fuel economy can
be achieved for LDVs through efforts to promote ‘eco-driving’ (An
etal., 2011; IEA, 2012d). Fuel efficiency improvements from eco-
driving for HDVs are in the 5 – 20 % range (AEA, 2011).
• Driving behaviour with new types of vehicles: Taking electric
vehicles (EVs) as an example, day / night recharging patterns and
the location of public recharging systems could affect how much
these vehicles are driven, when and where they are driven, and
potentially their GHG emissions impacts (Axsen and Kurani, 2012).
• Driving rebound effects: Reactions to lowering the cost of travel
(through fuel economy measures or using budget airline opera-
tors) can encourage more travel, commonly known as the (direct)
rebound effect (Greene etal., 1999; for a general discussion of the
rebound effect see Section 5.6.1). In North America, fuel cost elas-
ticity is in the range of a – 0.05 to – 0.30 (e. g., a 50 % cut in the
fuel cost would result in a 2.5 % to 15 % increase in driving). Sev-
eral studies show it is declining (Hughes etal., 2006; Small and van
Dender, 2007; EPA, 2012). The rebound effect is larger when the
marginal cost of driving (mostly gasoline) is a high share of house-
hold income. The implication for non-OECD countries is that the
price elasticity of demand for vehicle travel will be a function of
household income. The rebound effect may be higher in countries
with more modal choice options or where price sensitivity is higher,
but research is poor for most countries and regions outside the
OECD. Minimizing the rebound can be addressed by fuel taxes or
road pricing that offset the lower travel costs created by efficiency
improvements or reduced oil prices (see Section 8.10) (Hochman
etal., 2010; Rajagopal etal., 2011; Chen and Khanna, 2012).
5
Should a BEV run out of stored energy, it is less easy to refuel than is an ICE
vehicle that runs out of gasoline. With typical ranges around 100 – 160 km, BEV
drivers can become anxious about failing to complete their journey.
onstrated to meet the very strict fuel specifications required (Takeshita
and Yamaji, 2008; Caldecott and Tooze, 2009). Technologies to produce
ligno-cellulosic, Fisher-Tropsch, algae-based, and other advanced bio-
fuels are in development, but may need another decade or more to
achieve widespread commercial use (IEA, 2011a). Bio-methane from
suitably purified biogas or landfill gas can also be used in natural gas
vehicles (REN21, 2012).
Biofuels have direct, fuel-cycle GHG emissions that are typically
30 – 90 % lower per kilometre travelled than those for gasoline or diesel
fuels. However, since for some biofuels, indirect emissions — including
from land use change — can lead to greater total emissions than when
using petroleum products, policy support needs to be considered on a
case by case basis (see Chapter 11.13 and, for example, Lapola etal.,
2010; Plevin etal., 2010; Wang etal., 2011; Creutzig etal., 2012a).
8�3�4 Comparative analysis
The vehicle and power-train technologies described above for reducing
fuel consumption and related CO
2
emissions span a wide range and
are not necessarily additive. When combined, and including different
propulsion and fuel systems, their overall mitigation potential can be
evaluated as an integrated fuel / vehicle system (see Section 8.6). How-
ever, to produce an overall mitigation evaluation of the optimal design
of a transport system, non-CO
2
emissions, passenger or freight occu-
pancy factors, and indirect GHG emissions from vehicle manufacture
and infrastructure should also be integrated to gain a full comparison
of the relative GHG emissions across modes (see Section 8.4; Hawkins
etal., 2012; Borken-Kleefeld etal., 2013).
Taking LDVs as an example, a comparative assessment of current and
future fuel consumption reduction potentials per kilometre has been
made (Figure 8.7), starting from a 2010 baseline gasoline vehicle at
about 8 lge
4
/ 100km and 195 g / km CO
2
. Using a range of technologies,
average new LDV fuel economy can be doubled (in units of distance
per energy, i. e., energy intensity cut by 50 %). Further improvements
can be expected for hybrids, PHEVs, BEVs, and FCVs, but several hur-
dles must be overcome to achieve wide market penetration (see Sec-
tion 8.8). Vehicle cost increases due to new technologies could affect
customers’ willingness to pay, and thus affect market penetration,
although cost increases would be at least partly offset by fuel cost sav-
ings (see Section 8.6).
8�3�5 Behavioural aspects
The successful uptake of more efficient vehicles, advanced technolo-
gies, new fuels, and the use of these fuels and vehicles in ‘real life’
conditions, involves behavioural aspects.
4
“Litre per gasoline equivalent” allows for a comparison between fuels with differ-
ent energy contents.
Figure 8�7 | Indicative fuel consumption reduction potential ranges for a number of
LDV technology drive-train and fuel options in 2010 and 2030, compared with a base-
line gasoline internal combustion engine (ICE) vehicle consuming 8 l / 100km in 2010.
(Based on Kobayashi etal., 2009; Plotkin etal., 2009; IEA, 2012b; NRC, 2013).
0%
0 20 40
8060
100
FCEV
BEV
Gasoline PHEV
Gasoline Hybrid
Diesel ICE
Gasoline ICE
FCEV
BEV
Gasoline PHEV
Gasoline Hybrid
Diesel ICE
Gasoline ICE
Change in Energy Use per Vehicle km [%]
2010
2030
618618
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Chapter 8
• Vehicle choice-related rebounds: Other types of rebound effect
are apparent, such as shifts to purchasing larger cars concurrent
with cheaper fuel or shifts from gasoline to diesel vehicles that give
lower driving costs (Schipper and Fulton, 2012). Shifts to larger
HDVs and otherwise less expensive systems can divert freight from
lower carbon modes, mainly rail, and can also induce additional
freight movements (Umweltbundesamt, 2007; TML, 2008; Leduc,
2009; Gillingham etal., 2013).
• Company behaviour: Behavioural change also has a business
dimension. Company decision making can exert a strong influence
on the level of transport emissions, particularly in the freight sec-
tor (Rao and Holt, 2005). Freight business operators have a strong
incentive to reduce energy intensity, since fuel typically accounts
for around one third of operating costs in the road freight sector,
40 % in shipping, and 55 % in aviation (Bretzke, 2011). The resulting
reductions in transport costs can cause a rebound effect and gener-
ate some additional freight movement (Matos and Silva, 2011). For
company managers to switch freight transport modes often requires
a tradeoff of higher logistics costs for lower carbon emissions
(Winebrake etal., 2008). Many large logistics service providers have
set targets for reducing the carbon intensity of their operations by
between 20 % and 45 % over the period from 2005 / 2007 to 2020,
(McKinnon and Piecyk, 2012) whereas many smaller freight opera-
tors have yet to act (Oberhofer and Fürst, 2012).
8.4 Infrastructure and
systemic perspectives
Transport modes, their infrastructures, and their associated urban fab-
ric form a system that has evolved into the cities and regions with
which we are most familiar. ‘Walking cities’ existed for 8000 years;
some are being reclaimed around their walkability (Gehl, 2011). ‘Tran-
sit cities’ were built and developed around trams, trolley buses, and
train systems since the mid 19th century (Cervero, 1998; Newman and
Kenworthy, 1999). ‘Automobile cities’ evolved from the advent of
cheap LDVs (Brueckner, 2000) and have become the dominant para-
digm since the 1950s, leading to automobile dependence and auto-
mobility (Urry, 2007). A region can be defined and understood in terms
of the transport links to ports and airports regardless of the number
and types of cities located there. In all cases, the inter-linkages
between transport infrastructure and the built environment establish
path dependencies, which inform long-term transport-related mitiga-
tion options. For a general discussion of urban form and infrastructure
see Chapter 12.4.
8�4�1 Path dependencies of infrastructure and
GHG emission impacts
Systemic change tends to be slow and needs to address path depen-
dencies embedded in sunk costs, high investment levels, and cultural
patterns. Technological and behavioural change can either adapt to
existing infrastructures, or develop from newly constructed infrastruc-
tures, which could provide an initial template for low carbon technolo-
gies and behaviour. Developments designed to improve infrastructure
in rapidly urbanizing developing countries will decisively determine
the future energy intensity of transport and concomitant emissions
(Lefèvre, 2009), and will require policies and actions to avoid lock-in.
The construction, operation, maintenance, and eventual disposal of
transport infrastructure (such as rail tracks, highways, ports, and air-
ports), all result in GHG emissions. These infrastructure-related emis-
sions are usually accounted for in the industry and building sectors.
However, full accounting of life cycle assessment (LCA) emissions
from a transport-perspective requires these infrastructure-related
emissions to be included along with those from vehicles and fuels
(see Section 8.3.5). GHG emissions per passenger-kilometre (p-km) or
per tonne-kilometre (t-km) depend, inter alia, on the intensity of use
of the infrastructure and the share of tunnels, bridges, runways, etc.
(Åkerman, 2011; Chang and Kendall, 2011; UIC, 2012). In the United
States, GHG emissions from infrastructure built for LDVs, buses, and
Table 8�1 | High-speed rail transport infrastructure GHG emissions based on LCA data.
Mode / component Emissions (gCO
2
eq / p-km) Reference Comment
Swedish high-speed rail plans for Europabanan
infrastructure
2.7
Amos etal., 2010; Åkerman,
2011
At 25 million passengers per year
Vehicle construction and maintenance emissions;
Swedish high-speed rail
1.0 Åkerman, 2011 Over full lifetime of high-speed rail vehicles
Inter-city express (ICE) system study (Germany and
surrounds)
9.7 Von Rozycki etal., 2003
About half total emissions arise from infrastructure including non-
high-speed stretches
High-speed rail infrastructure (Europe) 3.1 – 10.9 Tuchschmid, 2009
Low emission value for 90 trains per track per day, high emission
value for 25. Current EU network is at 6.3 g / p-km
US high-speed rail plans 3.2 g / p-km Chang and Kendall, 2011 This 725 km line will emit 2.4 MtCO
2
eq / yr
Note: Since LCA assumptions vary, the data can only be taken as indicative and not compared directly.
619619
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8
Chapter 8
air transport amount to 17 – 45 gCO
2
eq / p-km, 3 – 17 gCO
2
eq / p-km, and
5 – 9 gCO
2
eq / p-km respectively (Chester and Horvath, 2009) with rail
typically between 3 – 11 gCO
2
eq / p-km (see Table 8.1). Other than for
rail, relevant regional infrastructure-related GHG emissions research on
this topic is very preliminary.
Opportunities exist to substantially reduce these infrastructure related
emissions, for instance by up to 40 % in rail (Milford and Allwood,
2010), by the increased deployment of low-carbon materials and recy-
cling of rail track materials at their end-of-life (Network Rail, 2009; Du
and Karoumi, 2012). When rail systems achieve modal shift from road
vehicles, emissions from the rail infrastructure may be partially offset
by reduced emissions from road infrastructures (Åkerman, 2011). To be
policy-relevant, LCA calculations that include infrastructure need to be
contextualized with systemic effects such as modal shifts (see Sections
8.4.2.3 and 8.4.2.4).
Existing vehicle stock, road infrastructure, and fuel-supply infrastruc-
ture prescribe future use and can lock-in emission paths for decades
while inducing similar investment because of economies of scale (Sha-
lizi and Lecocq, 2009). The life span of these infrastructures ranges
from 50 to more than 100 years. This range makes the current develop-
ment of infrastructure critical to the mode shift opportunities of the
future. For example, the successful development of the United States
interstate highway system resulted in a lack of development of an
extensive passenger rail system, and this determined a demand-side
lock-in produced by the complementarity between infrastructure and
vehicle stock (Chapter 12.3.2). The construction of the highway sys-
tem accelerated the growth of road vehicle kilometres travelled (VKT)
around 1970, and ex-urban development away from city centres cre-
ated a second peak in road transport infrastructure investment post
1990 (Shalizi and Lecocq, 2009). Conversely, the current rapid develop-
ment of high-speed rail infrastructure in China (Amos etal., 2010) may
provide low emission alternatives to both road transport and aviation.
Substantial additional rail traffic has been generated by constructing
new lines (Chapter 12.4.2.5), although a net reduction of emissions
will only occur after achieving a minimum of between 10 and 22 mil-
lion passengers annually (Westin and Kågeson, 2012).
Aviation and shipping require less fixed infrastructures and hence tend
to have a relative low infrastructure share of total lifecycle emissions.
Rising income and partially declining airfares have led to increased
air travel (Schäfer etal., 2009), and this correlates not only with new
construction and expansion of airports, but also with shifting norms in
travel behaviour (Randles and Mander, 2009).
8�4�2 Path dependencies of urban form and
mobility
Transport demand and land use are closely inter-linked. In low-density
developments with extensive road infrastructure, LDVs will likely domi-
nate modal choice for most types of trips. Walking and cycling can be
made easier and safer where high accessibility to a variety of activi-
ties are located within relative short distances (Ewing and Cervero,
2010) and when safe cycle infrastructure and pedestrian pathways
are provided (Tiwari and Jain, 2012; Schepers etal., 2013). Conversely
the stress and physical efforts of cycling and walking can be greater
in cities that consistently prioritize suburban housing developments,
which leads to distances that accommodate the high-speed movement
and volume of LDVs (Naess, 2006). In developing countries, existing
high-density urban patterns are conducive to walking and cycling, both
with substantial shares. However, safe infrastructure for these modes is
often lacking (Thynell etal., 2010; Gwilliam, 2013). Sustainable urban
planning offers tremendous opportunities (reduced transport demand,
improved public health from non-motorized transport (NMT), less air
pollution, and less land use externalities) (Banister, 2008; Santos etal.,
2010; Bongardt et al., 2013; Creutzig etal., 2012a). As an example,
an additional 1.1 billion people will live in Asian cities in the next 20
years (ADB, 2012a) and the majority of this growth will take place in
small-medium sized cities that are at an early stage of infrastructure
development. This growth provides an opportunity to achieve the long-
term benefits outlined above (Grubler etal., 2012) (see also 8.7 and
Chapter 12.4.1).
Urban population density inversely correlates with GHG emissions
from land transport (Kennedy etal., 2009; Rickwood etal., 2011) and
enables non-motorized modes to be more viable (Newman and Ken-
worthy, 2006). Disaggregated studies that analyze individual transport
use confirm the relationship between land use and travel (Echenique
etal., 2012). Land use, employment density, street design and con-
nectivity, and high transit accessibility also contribute to reducing car
dependence and use (Handy etal., 2002; Ewing, 2008; Cervero and
Murakami, 2009; Olaru etal., 2011). The built environment has a major
impact on travel behaviour (Naess, 2006; Ewing and Cervero, 2010),
but residential choice also plays a substantial role that is not easy
to quantify (Cao etal., 2009; Ewing and Cervero, 2010). There exists
a non-linear relationship between urban density and modal choice
(Chapter 12.4.2.1). For example, suburban residents drive more and
walk less than residents living in inner city neighbourhoods (Cao etal.,
2009), but that is often true because public transit is more difficult
to deploy successfully in suburbs with low densities (Frank and Pivo,
1994). Transport options that can be used in low density areas include
para-transit
6
and car-sharing, both of which can complement individu-
alized motorized transport more efficiently and with greater customer
satisfaction than can public transit (Baumgartner and Schofer, 2011).
Demand-responsive, flexible transit, and car sharing services can have
lower GHG emissions per passenger kilometre with higher quality ser-
vice than regional public transport (Diana etal., 2007; Mulley and Nel-
son, 2009; Velaga etal., 2012; Loose, 2010).
6
Para-transit, also called “community-transit”, is where flexible passenger transport
minibuses (also termed matatus and marshrutkas), shared taxis, and jitneys
operate in areas with low population density without following fixed routes or
schedules.
620620
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The number of road intersections along the route of an urban jour-
ney, the number of destinations within walking distance, and land use
diversity issues have been identified as key variables for determining
the modal choice of walking (Ewing and Cervero, 2010). Public trans-
port use in the United States is related to the variables of street net-
work design and proximity to transit. Land use diversity is a secondary
factor.
8�4�2�1 Modal shift opportunities for passengers
Small but significant modal shifts from LDVs to bus rapid transit (BRT)
have been observed where BRT systems have been implemented.
Approximately 150 cities worldwide have implemented BRT systems,
serving around 25 million passengers daily (Deng and Nelson, 2011;
BRT Centre of Excellence, EMBARQ, IEA and SIBRT, 2012). BRT systems
can offer similar benefits and capacities as light rail and metro systems
at much lower capital costs (Deng and Nelson, 2011), but usually with
higher GHG emissions (depending on the local electricity grid GHG
emission factor) (Table 8.2). High occupancy rates are an important
requirement for the economic and environmental viability of public
transport.
Public transit, walking, and cycling are closely related. A shift from
non-motorized transport (NMT) to LDV transport occurred during the
20th century, initially in OECD countries and then globally. However,
a reversion to cycling and walking now appears to be happening in
many cities — mostly in OECD countries — though accurate data is
scarce (Bassett etal., 2008; Pucher etal., 2011). Around 90 % of all
public transit journeys in the United States are accompanied with a
walk to reach the final destination and 70 % in Germany (Pucher and
Buehler, 2010). In Germany, the Netherlands, Denmark, and elsewhere,
the cycling modal share of total trips has increased since the 1970s
and are now between 10 – 25 % (Pucher and Buehler, 2008). Some car-
bon emission reduction has resulted from cycle infrastructure deploy-
ment in some European cities (COP, 2010; Rojas-Rueda etal., 2011;
Creutzig etal., 2012a) and in some cities in South and North America
(USCMAQ, 2008; Schipper etal., 2009; Massink etal., 2011; USFHA,
2012). Walking and cycling trips vary substantially between countries,
accounting for over 50 % of daily trips in the Netherlands and in many
Asian and African cities (mostly walking); 25 – 35 % in most European
countries; and approximately 5 – 10 % in the United States and Aus-
tralia (Pucher and Buehler, 2010; Leather etal., 2011; Pendakur, 2011;
Mees and Groenhart, 2012).
The causes for high modal share of NMT differ markedly between
regions depending on their cultures and characteristics. For example,
they tend to reflect low-carbon urban policies in OECD countries such
as the Netherlands, while reflecting a lack of motorization in devel-
oping countries. Land use and transport policies can influence the
bicycle modal share considerably (Pucher and Buehler, 2006), most
notably by the provision of separate cycling facilities along heavily
traveled roads and at intersections, and traffic-calming of residential
neighbourhoods (Andrade et al., 2011; NRC, 2011b)� Many Indian
and Chinese cities with traditionally high levels of walking are now
reporting dramatic decreases in this activity (Leather et al., 2011),
with modal shifts to personal transport including motorbikes and
LDVs. Such shifts are to some degree inevitable, and are in part desir-
able as they reflect economic growth. However, the maintenance of a
healthy walking and cycling modal share could be a sign of a liveable
and attractive city for residents and businesses (Bongardt etal., 2011;
Gehl, 2011).
Deliberate policies based around urban design principles have
increased modal shares of walking and cycling in Copenhagen, Mel-
bourne, and Bogota (Gehl, 2011). Public bicycle share systems have
created a new mode for cities (Shaheen etal., 2010), with many cit-
ies now implementing extensive public cycling infrastructure, which
results in increased bicycle modal share (DeMaio, 2009). Revising elec-
tric bicycle standards to enable higher performance could increase the
feasible commuting range and encourage this low emissions personal
transport mode. Electric bicycles offer many of the benefits of LDVs in
terms of independence, flexibility of routes, and scheduling freedom,
but with much lower emissions and improved health benefits.
With rising income and urbanization, there will likely be a strong pull
toward increasing LDV ownership and use in many developing coun-
tries. However, public transit mode shares have been preserved at fairly
high levels in cities that have achieved high population densities and
that have invested heavily in high quality transit systems (Cervero,
2004). Their efficiency is increased by diverse forms of constraints
on LDVs, such as reduced number of lanes, parking restrictions, and
limited access (La Branche, 2011). Investments in mass rapid transit,
timed with income increases and population size / density increases,
Table 8�2 | Comparison of capital costs, direct CO
2
emissions, and capacities for BRT, light rail, and metro urban mass transit options (IEA, 2012e).
Bus rapid transit Light rail Metro
Capital cost (million USD
2010
/ km) 5 – 27 13 – 40 27 – 330
Length of network that can be constructed for 1 USD
2010
billion cost (km) 37 – 200 25 – 77 3 – 37
World network length in 2011 (km) 2,139 15,000 10,000
Direct CO
2
intensity (gCO
2
/ p-km) 14 – 22 4 – 22 3 – 21
Capacity (thousand passengers per hour per direction) 10 – 35 2 – 12 12 – 45
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have been successful in some Asian megacities (Acharya and Morichi,
2007). As traffic congestion grows and freeway infrastructure reaches
physical, political, and economic limits, the modal share of public tran-
sit has increased in some OECD countries (Newman and Kenworthy,
2011b).
High-speed rail can substitute for short-distance passenger air travel
(normally up to around 800 km but also for the 1500 km in the case
of Beijing to Shanghai), as well as for most road travel over those
distances, and hence can mitigate GHG emissions (McCollum etal.,
2010; IEA, 2008). With optimized operating speeds and long distances
between stops, and high passenger load factors, energy use per pas-
senger-km could be as much as 65 to 80 % less than air travel (IEA,
2008). A notable example is China, which has shown a fast develop-
ment of its high-speed rail system. When combined with strong land-
use and urban planning, a high-speed rail system has the potential
to restructure urban development patterns, and may help to alleviate
local air pollution, noise, road, and air congestion (McCollum etal.,
2010).
8�4�2�2 Modal shift opportunities for freight
Over the past few decades, air and road have increased their global
share of the freight market at the expense of rail and waterborne
transport (European Environment Agency, 2011; Eom etal., 2012). This
has been due to economic development and the related change in the
industry and commodity mix, often reinforced by differential rates of
infrastructure improvement and the deregulation of the freight sector,
which typically favours road transport. Inducing a substantial reversal
of recent freight modal split trends will be difficult, inter alia because
of ‘structural inelasticity’ which confines shorter distance freight move-
ments to the road network because of its much higher network density
(Rich etal., 2011). If growth in global truck travel between 2010 and
2050 could be cut by half from the projected 70 % and shifted to
expanded rail systems, about a 20 % reduction in fuel demand and CO
2
could be achieved, with only about a fifth of this savings being offset
by increased rail energy use (IEA, 2009). The European Commission
(EC) set an ambitious target of having all freight movements using rail
or waterborne modes over distances greater than 300 km by 2030,
leading to major changes in modal shares (Figure 8.8) (Tavasszy and
Meijeren, 2011; EC, 2013).
The capacity of the European rail network would have to at least dou-
ble to handle this increase in freight traffic and the forecast growth
in rail passenger volumes, even if trains get longer and run empty
less often (den Boer etal., 2011). Longer-term transformations need
to take account of the differential rates at which low-carbon technol-
ogies could impact on the future carbon intensity of freight modes.
Applying current average energy intensity values (Section 8.3.1) may
result in over-estimates of the potential carbon benefits of the modal
shift option. Although rail freight generates far lower GHG emissions
per tonne-kilometre than road (Table 8.3), the rate of carbon-related
technical innovation, including energy efficiency improvements, has
been faster in HDV than rail freight and HDV replacement rate is typi-
cally much shorter, which ensures a more rapid uptake of innovation.
The potential for shifting freight to greener modes is difficult in urban
areas. Improvements in intra-urban rail freight movements are pos-
sible (Maes and Vanelslander, 2011), but city logistical systems are
almost totally reliant on road vehicles and are likely to remain so. The
greater the distance of land haul for freight, the more competitive
the lower carbon modes become. Within cities, the concept of modal
split between passenger and freight movement can be related to the
interaction. Currently, large amounts of freight on the so-called ‘last
mile’ to a home or business are carried by shoppers in LDVs and pub-
lic transport vehicles. With the rapid growth of on-line retailing, much
private car-borne freight, which seldom appears in freight transport
statistics, will be transferred to commercial delivery vans. Comparative
analyses of conventional and on-line retailing suggest that substitut-
ing a van delivery for a personal shopping trip by private car can yield
a significant carbon saving (Edwards etal., 2010).
At the international level, opportunities for switching freight from air
to shipping services are limited. The two markets are relatively discrete
and the products they handle have widely differing monetary values
and time-sensitivity. The deceleration of deep-sea container vessels
in recent years in accordance with the ‘slow steaming’ policies of the
shipping lines has further widened the transit time gap between sea
and air services. Future increases in the cost of fuel may, however,
encourage businesses to economize on their use of air-freight, pos-
sibly switching to sea-air services in which products are air-freighted
for only part of the way. This merger of sea and air transport offers
substantial cost and CO
2
savings for companies whose global supply
chains are less time-critical (Conway, 2007; Terry, 2007).
Figure 8�8 | Projected freight modal split in the EU-25 in 2030 comparing 2011 shares
with future business-as-usual shares without target and with EU White Paper modal
split target. Source: Based on Tavasszy and Meijeren, 2011.
Shares of Freight Movements by Mode [%]
0
10
20
30
40
50
60
70
80
If Target is MetWithout TargetActual 2011
Inland Waterway
Rail
Road
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Chapter 8
8.5 Climate change feed-
back and interaction
with adaptation
Transport is impacted by climate change both positively and negatively.
These impacts are dependent on regional variations in the nature and
degree of climate change and the nature of local transport infrastruc-
ture and systems. Adapting transport systems to the effects of climate
in some cases complement mitigations efforts while in others they
have a counteracting effect. Little research has so far been conducted
on the inter-relationship between adaptation and mitigation strategies
in the transport sector.
8�5�1 Accessibility and feasibility of transport
routes
Decreases in the spatial and temporal extent of ice cover in the Arctic
and Great Lakes region of North America regions are opening new and
shorter shipping routes over longer periods of the year (Drobot etal.,
2009; Stephenson etal., 2011). The expanded use of these routes could
reduce GHG emissions due to a reduction in the distance travelled. For
example, the Northern Sea Route (NSR) between Shanghai and Rot-
terdam is approximately 4,600 km shorter (about 40 %) than the route
via the Suez Canal. The NSR passage takes 18 – 20 days compared to
28 – 30 days via the southern route (Verny and Grigentin, 2009). Cli-
mate change will not only affect ice coverage, but may also increase
the frequency and severity of northern hemisphere blizzards and arctic
cyclones, deterring use of these shorter routes (Wassmann, 2011; Liu
etal., 2012). It is, nevertheless, estimated that the transport of oil and
gas through the NSR could increase from 5.5Mt in 2010 to 12.8 Mt
by 2020 (Ho, 2010). The passage may also become a viable option for
other bulk carriers and container shipping in the near future (Verny
& Grigentin, 2009; Schøyen & Bråthen, 2011). The economic viability
of the NSR is still uncertain without assessments of potentially prof-
itable operation (Liu and Kronbak, 2010) and other more pessimistic
prospects for the trans-Arctic corridors (Econ, 2007). One possible
negative impact would be that the increase in shipping through these
sensitive ecosystems could lead to an increase in local environmental
and climate change impacts unless additional emissions controls are
introduced along these shipping routes (Wassmann, 2011). Of spe-
cific concern are the precursors of photochemical smog in this polar
region that could lead to additional local positive regional climate forc-
ing (Corbett etal., 2010) and emissions of black carbon (see Section
8.2.2.1). Measurement methods of black carbon emissions from ships
and additional work to evaluate their impact on the Arctic are needed
before possible control measures can be investigated.
Changes in climate are also likely to affect northern inland waterways
(Millerd, 2011). In summer, these effects are likely to adversely affect
waterborne craft when reductions in water levels impair navigabil-
ity and cut capacity (Jonkeren etal., 2007; Görgen etal. 2010; Nilson
etal., 2012). On the other hand, reduced winter freezing can benefit
inland waterway services by extending the season. The net annual
effect of climate change on the potential for shifting freight to this
low-carbon mode has yet to be assessed.
8�5�2 Relocation of production and
reconfiguration of global supply chains
Climate change will induce changes to patterns of agricultural produc-
tion and distribution (Ericksen etal., 2009; Hanjra and Qureshi, 2010;
Tirado etal., 2010; Nielsen and Vigh, 2012; Teixeira etal., 2012). The
effect of these changes on freight transport at different geographi-
cal scales are uncertain (Vermeulen et al., 2012). In some scenarios,
food supply chains become longer, generating more freight movement
(Nielsen and Vigh, 2012; Teixeira etal., 2012). These and other long
supply lines created by globalization could become increasingly vulner-
able to climate change. A desire to reduce climate risk may be one of
several factors promoting a return to more localized sourcing in some
sectors (World Economic Forum and Accentura, 2009), a trend that
would support mitigation. Biofuel production may also be adversely
affected by climate change inhibiting the switch to lower carbon fuels
(de Lucena etal., 2009).
8�5�3 Fuel combustion and technologies
Increased ambient temperatures and humidity levels are likely to affect
nitrogen oxide, carbon monoxide, methane, black carbon, and other
particulate emissions from internal combustion engines and how these
gases interact with the atmosphere (Stump etal., 1989; Rakopoulos,
1991; Cooper and Ekstrom, 2005; Motallebi etal., 2008; Lin and Jeng,
1996; McCormick etal., 1997; Pidolal, 2012). Higher temperatures also
lead to higher evaporative emissions of volatile organic compound
emissions (VOCs) (Roustan etal., 2011) and could lead to higher ozone
levels (Bell etal., 2007). The overall effects are uncertain and could be
positive or negative depending on regional conditions (Ramanathan &
Carmichael, 2008).
As global average temperatures increase, the demand for on-board
cooling in both private vehicles and on public transport will increase.
The heating of vehicles could also grow as the frequency and sever-
ity of cold spells increase. Both reduce average vehicle fuel efficien-
cies. For example, in a passenger LDV, air-conditioning can increase
fuel consumption by around 3 – 10 % (Farrington and Rugh, 2000; IEA,
2009). Extremes in temperature (both high and low) negatively impact
on the driving range of electric vehicles due to greater use of on-board
heating and air conditioning, and thus will require more frequent
recharging. In the freight sector, energy consumption and emissions
in the refrigeration of freight flows will also increase as the extent and
degree of temperature-control increases across the supply chains of
food and other perishable products (James and James, 2010).
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8�5�4 Transport infrastructure
Climate proofing and adaptation will require substantial infrastruc-
ture investments (see Section 8.4 and the Working Group II (WGII)
Contribution to the IPCC Fifth Assessment Report (AR5), Chapter 15).
This will generate additional freight transport if implemented outside
of the normal infrastructure maintenance and upgrade cycle. Climate
proofing of transport infrastructure can take many forms (ADB, 2011a;
Highways Agency, 2011) varying in the amount of additional freight
movement required. Resurfacing a road with more durable materials
to withstand greater temperature extremes may require no additional
freight movement, whereas re-routing a road or rail link, or installing
flood protection, are likely to generate additional logistics demands,
which have yet to be quantified.
Adaptation efforts are likely to increase transport infrastructure costs
(Hamin & Gurran, 2009), and influence the selection of projects for
investment. In addition to inflating maintenance costs (Jollands etal.,
2007; Larsen etal., 2008), climate proofing would divert resources that
could otherwise be invested in extending networks and expanding
capacity. This is likely to affect all transport modes to varying degrees.
If, for example, climate proofing were to constrain the development of
a rail network more than road infrastructure, it might inhibit a modal
shift to less carbon-intensive rail services.
The future choice of freight and passenger traffic between modes may
also become more responsive to their relative sensitivity to extreme
weather events (Koetse and Rietveld, 2009; Taylor and Philp, 2010).
The exposure of modes to climate risks include aviation (Eurocontrol,
2008), shipping (Becker etal., 2012), and land transport (Hunt and
Watkiss, 2011). Little attempt has been made to conduct a compara-
tive analysis of their climate risk profiles, to assess the effects on the
modal choice behaviour of individual travellers and businesses, or to
take account of regional differences in the relative vulnerability of dif-
ferent transport modes to climate change (Koetse and Rietveld, 2009).
Overall, the transport sector will be highly exposed to climate change
and will require extensive adaptation of infrastructure, operations,
and service provision. It will also be indirectly affected by the adapta-
tion and decarbonization of the other sectors that it serves. Within the
transport sector there will be a complex interaction between adapta-
tion and mitigation efforts. Some forms of adaptation, such as infra-
structural climate proofing, will be likely to generate more freight and
personal movement, while others, such as the NSR, could substantially
cut transport distances and related emissions.
8.6 Costs and potentials
For transport, the potential for reducing GHG emissions, as well as the
associated costs, varies widely across countries and regions. Appropri-
ate policies and measures that can accomplish such reductions also
vary (see Section 8.10) (Kahn Ribeiro etal., 2007; Li, 2011). Mitigation
costs and potentials are a function of the stringency of climate goals and
their respective GHG concentration stabilization levels (Fischedick etal.,
2011; Rogelj etal., 2013). This section presents estimates of mitigation
potentials and associated costs from the application of new vehicle and
fuel technologies, performance efficiency gains, operational measures,
logistical improvements, electrification of modes, and low-carbon fuels
and activity reduction for different transport modes (aviation, rail, road,
waterborne and cross-modal). Potential CO
2
eq emissions reductions
from passenger-km (p-km) and tonne-km (t-km) vary widely by region,
technology, and mode according to how rapidly the measures and appli-
cations can be developed, manufactured, and sold to buyers replacing
existing ones in vehicles an fuels or adding to the total fleet, and on the
way they are used given travel behaviour choices (Kok etal., 2011). In
general, there is a larger emission reduction potential in the transport
sector, and at a lower cost, compared to the findings in AR4 (Kahn Ribeiro
etal., 2007).
The efforts undertaken to reduce activity, to influence structure and modal
shift, to lower energy intensity, and to increase the use of low-carbon
fuels, will influence future costs and potentials. Ranges of mitigation
potentials have an upper boundary based on what is currently understood
to be technically achievable, but will most likely require strong policies to
be achieved in the next few decades (see Section 8.10). Overall reductions
are sensitive to per-unit transport costs (that could drop with improved
vehicle efficiency); resulting rebound effects; and shifts in the type, level,
and modal mix of activity. For instance, the deployment of more efficient,
narrow-body jet aircraft could increase the number of commercially-
attractive, direct city-to-city connections, which may result in an overall
increase in fleet fuel use compared to hub-based operations.
This assessment follows a bottom-up approach to maintain consis-
tency in assumptions. Table 8.3 outlines indicative direct mitigation
costs using reference conditions as baselines, and illustrative examples
of existing vehicles and situations for road, aviation, waterborne, and
rail (as well as for some cross-mode options) available in the literature.
The data presented on the cost-effectiveness of different carbon reduc-
tion measures is less detailed than data on the potential CO
2
eq savings
due to literature gaps. The number of studies assessing potential future
GHG reductions from energy intensity gains and use of low-carbon
fuels is larger than those assessing mitigation potentials and cost from
transport activity, structural change and modal shift, since they are
highly variable by location and background conditions.
Key assumptions made in this analysis were:
• cost estimates are based on societal costs and benefits of tech-
nologies, fuels, and other measures, and take into account initial
costs as well as operating costs and fuel savings;
• existing transport options are compared to current base vehicles
and activities, whereas future options are compared to estimates
of baseline future technologies and other conditions;
624624
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Chapter 8
• fuel price projections are based on the IEA World Energy Outlook
(IEA, 2012b) and exclude taxes and subsidies where possible;
• discount rates of 5 % are used to bring future estimates back to
present (2013) values, though the literature considered has exam-
ined these issues mostly in the developed-world context; and
• indirect responses that occur through complex relationships within
sectors in the larger socioeconomic system are not included (Stepp
etal., 2009).
Results in Table 8.3 indicate that, for LDVs, efficiency improvement
potentials of 50 % in 2030 are technically possible compared to 2010,
with some estimates in the literature even higher (NRC, 2010). Virtu-
ally all of these improvements appear to be available at very low, or
even negative, societal costs. Electric vehicles have a CO
2
eq reduc-
tion cost highly correlated with the carbon intensity of electricity
generation: using relatively high-carbon intensity electricity systems
(500 – 600 gCO
2
eq / kWh), EVs save little CO
2
eq compared to conven-
tional LDVs and the mitigation cost can be many hundreds of dollars
per tonne; for very low-carbon electricity (below 200 gCO
2
eq / kWh) the
mitigation cost drops below 200 USD
2010
/ tCO
2
eq. In the future, with
lower battery costs and low-carbon electricity, EVs could drop below
100 USD
2010
/ tCO
2
eq and even approach zero net cost.
For long-haul HDVs, up to a 50 % reduction in energy intensity by 2030
appears possible at negative societal cost per tCO
2
eq due to the very
large volumes of fuel they use. HDVs used in urban areas where their
duty cycle does not require as much annual travel (and fuel use), have
a wider range of potentials and costs, reaching above 100 USD
2010
/ t
CO
2
eq. Similarly, inter-city buses use more fuel annually than urban
buses, and as a result appear to have more low-cost opportunities for
CO
2
eq reduction (IEA, 2009; NRC, 2010; TIAX, 2011).
Recent designs of narrow and wide-body commercial aircraft are sig-
nificantly more efficient than the models they replace, and provide
CO
2
eq reductions at net negative societal cost when accounting for
fuel savings over 10 – 15 years of operation at 5 % discount rate. An
additional 30 – 40 % CO
2
eq reduction potential is expected from future
new aircraft in the 2020 – 2030 time frame, but the mitigation costs
are uncertain and some promising technologies, such as open rotor
engines, appear expensive (IEA, 2009; TOSCA, 2011).
For virtually all types of ocean-going ships including container vessels,
bulk carriers, and oil tankers, the potential reduction in CO
2
eq emis-
sions is estimated to be over 50 % taking into account a wide range of
technology and operational changes. Due to the large volume of fuel
used annually by these ships, the net cost of this reduction is likely to
be negative (Buhaug and et. al, 2009; Crist, 2009).
Key factors in the long term decarbonization of rail transport will be
the electrification of services and the switch to low-carbon electric-
ity generation, both of which will vary widely by country. Potential
improvements of 35 % energy efficiency for United States rail freight,
46 % for European Union rail freight and 56 % for EU passenger rail
services have been forecast for 2050 (Anderson etal., 2011; Vyas etal.,
2013). The EU improvements will yield a 10 – 12 % reduction in operat-
ing costs, though no information is available on the required capital
investment in infrastructure and equipment.
Regarding fuel substitution in all modes, some biofuels have the poten-
tial for large CO
2
eq reduction, although net GHG impact assessments
are complex (see Sections 8.3 and 11.13). The cost per tonne of CO
2
eq
avoided will be highly dependent on the net CO
2
eq reduction and the
relative cost of the biofuel compared to the base fuel (e. g., gasoline or
diesel), and any technology changes required to the vehicles and fuel
distribution network in order to accommodate new fuels and blends.
The mitigation cost is so sensitive that, for example, while an energy
unit of biofuel that cuts CO
2
eq emissions by 80 % compared to gas-
oline and costs 20 % more has a mitigation cost of about 80 USD / t
CO
2
eq, if the biofuel’s cost drops to parity with gasoline, the mitigation
cost drops to 0 USD / t CO
2
eq (IEA, 2009).
The mitigation potentials from reductions in transport activity con-
sider, for example, that “walking and cycle track networks can provide
20 % (5 – 40 % in sensitivity analyses) induced walking and cycle jour-
neys that would not have taken place without the new networks, and
around 15 % (0 – 35 % in sensitivity analyses) of current journeys less
than 5 km made by car or public transport can be replaced by walking
or cycling” (Sælensminde, 2004). Urban journeys by car longer than
5 km can be replaced by combined use of non-motorized and intermo-
dal public transport services (Tirachini and Hensher, 2012).
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Table 8�3 | Selected CO
2
eq mitigation potentials and costs for various modes in the transport sector with baselines of stock average fleet compared with 2010 new vehicles and 2030 projected vehicle based on available data. (See foot-
notes at end of Table).
050100150200250
Emissions intensity (gCO
2
eq/p-km)
-400 0 400 800 1200
2010 Stock average SUV
2010 Stock average LDV
2010 Stock average 2 Wheeler
LCCC* [USD
2010
/tCO
2
eq]
Indicative direct mitigation cost in
relation to the baseline
(can be positive or negative)
Indicative 2010 stock average baseline
CO
2
eq emissions and reduction potential
BRT system, Bogota, Colombia
has emission reductions of
250,000 tCO
2
eq/yr (12).
BRT infrastructure cost: 1–27 million USD/km (13).
Benefit-cost-ratios of selected BRT systems:
Hamilton, Canada 0.37–1.34;
Canberra, Australia 1.98–4.78 (12, 36)
Average CO
2
emissions level
of new cars in the EU decreased
from 170 gCO
2
/km in 2001 to
136 gCO
2
/km in 2011 (43, 47)
New mid-size gasoline:
2012 Toyota Yaris hybrid;
79 gCO
2
/p-km (6).
New mid-size Diesel:
Volkswagen Golf Blue motion
1.6 TDI: 99 gCO
2
/p-km (6)
EVs:
2013 Nissan Leaf: 24 kWh has
175 km range on New European
Driving Cycle, ranging from
76 to 222 km depending on
driving conditions (6).
Baseline 2010 stock average vehicles
Industry average; 164 gCO
2
/p-km (6).
Drive-train redesigns may yield 25% improvement.
Additional reductions from light-weighting, aerodynamics,
more efficient accessories (6). Most current and many
future LDV efficiency improvements are at negative cost
of USD/tCO
2
(4, 47). Potential 40–60% fuel efficiency
gains by 2030 compared to similar size 2010 LDVs (5).
2030 conventional/hybrid:
- mid-size; 70–120 gCO
2
/p-km (25).
2010 EV:
- 80–125 gCO
2
/p-km using high-carbon electricity grid at
600 gCO
2
/kWh;
- 28–40 gCO
2
/p-km using low-carbon grid electricity at
200 gCO
2
/kWh.
Likely over 200 USD/tCO
2
in 2010 even with low-carbon
grid electricity.
2030 EV:
- 55–235 USD/tCO
2
with high-carbon electricity.
- 0–100 USD/tCO
2
with low-carbon electricity (5).
EV efficiency 0.2–0.25 kWh/km on road (7).
Battery cost:
- 750 USD/kWh in 2010;
- 200–300 USD /kWh in 2030 (11).
Vehicle intensity (well-to-wheel) of 144–180 gCO
2
/100km at
0.20–0.25 kWh/km.
PHEV:
15–70% well-to-wheel more efficient than baseline ICEV (7);
28–50% more efficient by 2030 (5).
Baseline: 2010 stock average scooters
Up to 200 cc typical for Asia (48).
30% savings in fuel
consumption for hybrid buses
in Montreal (14).
Baseline: 2010 stock average medium haul bus
40-passenger occupancy vehicle.
Potential efficiency improvement 0–30%.
Mitigation options in
passenger transport
Illustrative examplesReference conditions
and assumptions made
2010 Diesel
2010 Hybrid diesel
2010 Gasoline
2010 Gasoline
2010 Gasoline
2030 Gasoline
2030 Gasoline
2030 Diesel
2030 Compressed natural gas
2010 Hybrid gasoline
2030 Hybrid gasoline
2010 Hybrid gasoline
2010 Diesel
2010 Compressed natural gas
2010 Electric, 600 g CO
2
eq/kWh
el
2010 Electric, 200 g CO
2
eq/kWh
el
2030 Hybrid gasoline
2030 Hybrid gasoline/biofuel* (50/50 share)
Road
New buses, large size
New sport utility vehicles (SUV), mid-size
New light duty vehicles (LDV), mid-size
Bus rapid transit (BRT)
New 2 wheeler
(Scooter up to 200 cm³ cylinder capacity)
2030 Electric, 200 gCO
2
eq/kWh
el
Optimized gasoline SUV (2030)
Optimized gasoline LDV (2030)
New gasoline SUV (2010)
New gasoline LDV (2010)
Baselines for LCCC calculation
*Levelized cost of conserved carbon (LCCC), here at 5% weighted average cost of capital (WACC)
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050100150200
Emissions intensity (gCO
2
eq/p-km)
-600 -400 -200 0 200
2010 Electric, 600 g CO
2
eq/kWh
el
2010 Electric, 200 g CO
2
eq/kWh
el
Rail (light rail car)
2010 Stock average
New current long-haul wide
body: Boeing 787 is 30%
more fuel efficient than
Boeing 767; Boeing 747-800
is 20% more efficient than
Boeing 747-400 (1, 51).
New 2010 medium-long-haul,
narrow body:
Airbus A320 and Boeing
737 (42).
European rail operations:
Passenger: 46% reduction in
GHG/p-km by 2050 with
11% reduction in operating
costs (43).
8% improvement via
regenerative braking systems
(Amtrak, US); 40% through
design and engine
improvements
(Shinkansen, Japan) (18).
35% reduction in energy
intensity - for US rail
operations (17).
Aviation
(Commercial, medium to long haul)
Operational measures
Baseline: 2010 stock average commercial (25)
Medium haul aircraft; 150-passenger occupancy; average
trip distance.
Aircraft efficiency: Incremental changes to engines and
materials up to 20% efficiency improvement. Most efficient
present aircraft designs provide 15–30% CO
2
emissions reductions
per revenue p-km compared to previous generation aircraft, at net
negative costs since fuel savings typically greater than cost of
improved technology. (5)
2030 next generation aircraft design: Advanced engines
up to 33% improvement; radical new designs such as ‘flying wing’,
up to 50% improvement. Medium and long-haul (narrow and
wide-body) aircraft compared to today’s best aircraft design:
- 20–35% CO
2
emissions reduction potential by 2025
for conventional aircraft
- up to 50% with advanced designs (e.g., flying wing)(2)
Costs: ~20% CO
2
reduction at <0–100 USD/tCO
2
(narrow body); ~33% reduction at <0–400 USD/tCO
2
(open rotor engine) (34).
Taxiing and flight operations including direct routing,
optimum altitude and speed; circling, landing patterns.
Improved ground equipment and auxiliary power units
can yield 6–12% fuel efficiency gains (3).
Baseline: 2010 electric medium haul train
- Based on electricity grid 600 gCO
2
/kWh: 3–20 gCO
2
/p-km (25).
2010 light rail; 60 passenger occupancy car:
- CO
2
reduction at 4–22 gCO
2
/p-km;
- Infrastructure cost 14–40 million USD/km (5).
2010 metro:
- CO
2
reduction 3–21 gCO
2
/p-km;
- Infrastructure cost 27–330 million USD/km (5).
2010 long-distance rail:
- 45–50% reduction in CO
2
/p-km (augmented if switch to
low-carbon electricity).
- 14% reduction in operating costs (allowing for increase in
speed and with energy costs excluded from cost calculation (38).
- 8–40% efficiency gains (12–19 gCO
2
/p-km).
- Infrastructure cost 4–75 million USD/km (5).
Potential GHG savings from eco-driving 15%; regenerative
braking 13%; mass reduction 6% (38).
Illustrative examplesReference conditions
and assumptions made
2010 Narrow and wide body
2030 Narrow body
2030 Narrow body, open rotor engine
Average new aircraft (2010)
Baselines for LCCC calculation
Indicative direct mitigation cost in
relation to the baseline
(can be positive or negative)
Indicative 2010 stock average baseline
CO
2
eq emissions and reduction potential
Mitigation options in
passenger transport
LCCC* [USD
2010
/tCO
2
eq]
*Levelized cost of conserved carbon (LCCC), here at 5% weighted average cost of capital (WACC)
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Emissions intensity (gCO
2
eq/t-km)
New diesel example (47)
New diesel hybrid example (47)
'Green Trucks Project'
Guangzhou, China, could save
8.6 billion l/yr of fuel and
reduce CO
2
emissions by 22.3
MtCO
2
/yr if all HDVs in the
province participated (12).
UK ‘Logistics Carbon
Reduction Scheme’
comprising 78 businesses
set target for reducing the
target intensity of road
freight transport by 8%
between 2010 and 2015,
which is likely to be achieved
by the end of 2013.
Baseline stock average medium haul HDV
Diesel fuelled HDVs: 76–178 gCO
2
/t-km (25).
55% improvement in energy efficiency of tractor
trailer HDV between 2010 and 2030 and 50% for other
categories of HDV (9, 10).
30–62% improvement by 2030 compared to a similar size 2007–
2010 HDV, including increasing load factor by up to 32% (5, 11).
Urban HDVs 30–50% reductions at 0–200 USD/tCO
2
.
Long-haul HDV up to 50% potential CO
2
reduction at
negative costs per tCO
2
saved.
Road
Mitigation options in
freight transport
Illustrative examplesReference conditions
and assumptions made
0200400
-100 1000 200
2010 stock average
2010 stock average
New heavy duty, long-haul trucks
New medium duty trucks
2010 Diesel
2010 Diesel hybrid
2010 Compressed natural gas
2010 Diesel
2010 Compressed natural gas
2030 Diesel/biofuel (50/50 share)**
2030 Diesel
2030 Diesel
**Assuming 70% Less CO
2
eq/MJ Biofuel than /MJ Diesel
New diesel long-haul (2010)
Baselines for LCCC calculation
Indicative direct mitigation cost in
relation to the baseline
(can be positive or negative)
Indicative 2010 stock average baseline
CO
2
eq emissions and reduction potential
LCCC* [USD
2010
/tCO
2
eq]
*Levelized cost of conserved carbon (LCCC), here at 5% weighted average cost of capital (WACC)
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Emissions intensity (gCO
2
eq/t-km)
2010 new medium vessel:(46)
Industry initiatives through the
Energy Efficiency Design Index
and Ship Energy Efficiency
Management Programme of
the International Maritime
Organisation (IMO)(22)
Global average speed reduction
of 15% would give benefits that
outweigh costs by 178–617
billion USD by 2050 (31).
'Slow steaming' at 10% slower
speed gives 15–19% CO
2
emissions reduction; 20%
slower speed gives 36–39%
(24, 31, 37).
Inland waterways potential (46)
Baseline: Stock average international ships
10–40 gCO
2
/t-km (25).
2010 water craft: 5–30% CO
2
/t-km reduction potential;
retrofit and maintenance measures 2–20%; total reduction
43% (2020) to 63% (2050) (19). Potential up to 60% CO
2
reduction by 2030 from optimized technology and operation
(19). 30% or more reduction in CO
2
/t-km by 2030 at zero
cost (30).
2030 water craft: Business-as-usual reduction in carbon
intensity of shipping of 20% between 2010 and 2030 but
could rise to 37% with industry initiatives (39).
Operations: Potential CO
2
reductions 15–39%;
Slow steaming at 3–9kts slower than 24kt baseline.
Cost savings around 200 USD/tCO
2
at bunker fuel price of
700 USD/t and combining savings for carriers and shippers (37).
CO
2
emissions reductions of 43% per t-km by 2020 (20);
- 63% CO
2
/t-km by 2050 (21);
- 25–75% GHG intensity by 2050 (22);
- 39–57 % CO
2
/t-km ‘attainable’ by 2050;
- 59–72 % CO
2
/t-km is ‘optimistic’ by 2050 (23)
See passenger “Rail
(Light Rail Car)” above
Baseline based on electricity grid 600 gCO
2
/kWh:
6–33 gCO
2
/t-km (25).
- 40–45% reduction in CO
2
/t-km (augmented if switch to
low-carbon electricity).
- 14% reduction in operating costs (allowing for increase in
speed and with energy costs excluded from cost calculation) (38).
Also see passenger “Rail (Light Rail Car)” above.
See Passenger “Aviation”
examples above
See Passenger “Aviation” assumptions above
Freight factors for wide-bodied passenger aircraft are around
15-30% whilst narrow bodied planes are typically 0-10% (52),
Mitigation options in
freight transport
Illustrative examplesReference conditions
and assumptions made
02004006008001000 -100-200 1000 300200 400
2010 Stock average
Aviation
(Commercial, medium to long haul)
Rail (freight train)
Waterborne
Water craft operations
and logistics
Slow steaming of container vessel.
Inland waterways
2010 Belly-hold
2010 Diesel, light goods
2010 Diesel, heavy goods
2010 Electric , 200 gCO
2
eq/kWh
el
2010 New large international container vessel
2010 Large bulk carrier/tanker
2010 LNG bulk carrier
2010 Dedicated airfreighter
2030 Improved aircraft
2030 Improved, open rotor engine
2030 Optimized container vessel
2030 Optimized bulk carrier
Average new aircraft (2010)
New bulk carrier/
container vessel (2010)
Baselines for LCCC calculation
Indicative direct mitigation cost in
relation to the baseline
(can be positive or negative)
Indicative 2010 stock average baseline
CO
2
eq emissions and reduction potential
LCCC* [USD
2010
/tCO
2
eq]
*Levelized cost of conserved carbon (LCCC), here at 5% weighted average cost of capital (WACC)
2010 Stock average international shipping
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Chapter 8
Brazilian sugarcane: 80%
GHG emissions reduction
compared with gasoline
(excluding land use change
effects) (33).
UK Government best practice
programme for freight/logistics
at –12 USD/tCO
2
(28).
Low-carbon technologies for
urban and long-haul road
freight –67–110 USD/tCO
2
;
Route management : ~330
USD/tCO
2
.
Japan: 12% fuel consumption
savings through eco-driving-
schemes in freight (12).
Urban densification in the USA
over about 50 years could
reduce fuel use by 9–16% (35).
0–100% excluding land use change effects (26, 33).
GHG reduction potential by fuel type:
- sugarcane ethanol: 0–80%
- enzymatic hydrolysis ethanol: 0–100%
- advanced biomass-to-liquid processes (direct gasoline/diesel
replacements): 0–100% (33). 80 USD/tCO
2
for biofuels with 80%
lower net GHG emissions and 20% higher cost per litre gasoline
equivalent (lge) than base fuel (e.g., gasoline).
13–330 USD/tCO
2
(26, 28).
~18% reduction in CO
2
/t-km possible from:
- speed reduction (7 percentage points)
- optimized networks (5 percentage points)
- modal switch (4 percentage points)
- increased home delivery (1 percentage point)
- reduced congestion (1 percentage point) (27).
Negative costs per tCO
2
saved even with on-board eco-drive
assistance technologies and meters (32).
5–10% reduced fuel consumption (50)
5–25% reduced fuel consumption (15, 16).
GHG reduction of up to 30% (29, 40, 41)
Biofuels
Logistics and freight
operations
Eco-driving and driver
education
Activity reduction in
urban areas
Cross-modal
mitigation options
Illustrative examplesReference conditions
and assumptions made
Indicative direct mitigation cost in
relation to the baseline
(can be positive or negative)
Indicative 2010 stock average baseline
CO
2
eq emissions and reduction potential
Broad range Broad range
Selected CO
2
eq mitigation potentials resulting from changes in transport modes with different emission intensities (tCO
2
eq / p-km or / t-km) and associated levelized cost of conserved carbon (LCCC in USD
2010
/ tCO
2
eq saved). Estimates are
indicative. Variations in emission intensities stem from variation in vehicle efficiencies and occupancy / load rates. Estimated LCCC for passenger road transport options are point estimates ± 100 USD
2010
/ tCO
2
eq based on central estimates
of input parameters that are very sensitive to assumptions (e. g., specific improvement in vehicle fuel economy to 2030, specific biofuel CO
2
eq intensity, vehicle costs, fuel prices). They are derived relative to different baselines (see legend
for colour coding) and need to be interpreted accordingly. Estimates for 2030 are based on projections from recent studies, but remain inherently uncertain. LCCC for aviation and for freight transport are taken directly from the literature.
Additional context to these estimates is provided in the two right-most columns of the table (see Annex III, Section A.III.3 for data and assumptions on emission intensities and cost calculations and Annex II, Section A.II.3.1 for methodologi-
cal issues on levelized cost metrics).
References: 1: IATA (2009), 2: TOSCA (2011), IEA (2009), 3: Dell’Olmo and Lulli (2003), Pyrialakou etal. (2012), 4: Bandivadekar (2008), ICCT (2010), Greene and Plotkin (2011), IEA (2012a), 5: IEA (2012), 6: NRC (2011a), 7: Sims etal.
(2011), 8: Chandler etal. (2006), 9: ICCT (2010), NRC (2010), IEA (2012e), 10: ICCT. (2012), 11: NRC (2012), 12: UNEP (2011), 13: Chandler etal. (2006), IPCC (2007), AEA (2011), ITF (2011), IEA (2012d), 14: Hallmark etal. (2013), 15:
Goodwin and Lyons (2010), Taylor and Philp (2010), Ashton-Graham etal. (2011), Höjer etal. (2011), Salter etal. (2011), Pandey (2006), 16: Behrendt et al. (2010), 17: Argonne National Lab. (2013), 18: UIC (2011), 19: IEA (2011a), 20:
Crist (2009), IMO (2009), DNV (2010), ICCT (2011b), Lloyds Register and DNV (2011), Eide etal. (2011), 21: Crist (2009), 22: IMO (2009), 23: Lloyds Register and DNV (2011), 24: DNV (2010), 25: TIAX (2009), IEA (2012c), 26: Lawson
etal. (2007), AEA (2011), 27: World Economic Forum / Accenture (2009), 28: Lawson etal. (2007), 29: TFL (2007), Eliasson (2008), Creutzig and He (2009), 30: IMO (2009), 31: Faber etal. (2012), 32: IEA (2009), IEA (2010b), 33: Bioenergy
Annex, Chapter 11; 34: TOSCA (2011), 35: Marshall (2011), 36: ITDP (2009), 37: Maloni etal. (2013), 38: Andersson etal. (2011), 39: Wang (2012b), 40: Sælensminde (2004), 41: Tirachini and Hensher (2012), 42: DfT (2010), 43: Andersson
etal. (2011), 44: Halzedine etal. (2009), 45: Sharpe (2010), 46: Skinner etal. (2010a), 47: Hill etal. (2012), 48: IEA (2012c), 49: Freight Transport Association (2013), 50: SAFED 2013; 51: NTM (2011), 52: Jardine (2009).
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8.7 Co-benefits, risks
and spillovers
Mitigation in the transport sector has the potential to generate syner-
gies and co-benefits with other economic, social, and environmental
objectives. In addition to mitigation costs (see Section 8.6), the deploy-
ment of mitigation measures will depend on a variety of other fac-
tors that relate to the broader objectives that drive policy choices. The
implementation of policies and measures can have positive or negative
effects on these other objectives — and vice versa. To the extent these
effects are positive, they can be deemed as ‘co-benefits’; if adverse
and uncertain, they imply risks. Potential co-benefits and adverse side
effects of alternative mitigation measures (Section 8.7.1), associated
technical risks and uncertainties (Section 8.7.2), and public percep-
tions (Section 8.7.3) can significantly affect investment decisions and
individual behaviour as well as influence the priority-setting of poli-
cymakers. Table 8.4 provides an overview of the potential co-benefits
and adverse side-effects of the mitigation measures that are assessed
in this chapter. In accordance with the three sustainable development
pillars described in Sections 4.2 and 4.8, the table presents effects on
objectives that may be economic, social, environmental, and health
related. The extent to which co-benefits and adverse side effects will
materialize in practice, and their net effect on social welfare, differ
greatly across regions. Both are strongly dependent on local circum-
stances and implementation practices as well as on the scale and pace
of the deployment of the different mitigation measures (see Section
6.6).
8�7�1 Socio-economic, environmental, and
health effects
Transport relies almost entirely on oil with about 94 % of transport
fuels being petroleum products (IEA, 2011b). This makes it a key area of
energy security concern. Oil is also a major source of harmful emissions
that affect air quality in urban areas (see Section 8.2) (Sathaye etal.,
2011). In scenario studies of European cities, a combination of pub-
lic transit and cycling infrastructures, pricing, and land-use measures
is projected to lead to notable co-benefits. These include improved
energy security, reduced fuel spending, less congestion, fewer acci-
dents, and increased public health from more physical activity, less air
pollution and less noise-related stress (Costantini etal., 2007; Greene,
2010b; Rojas-Rueda et al., 2011; Rojas-Rueda etal., 2012; Creutzig
etal., 2012a). However, only a few studies have assessed the associ-
ated welfare effects comprehensively and these are hampered by data
uncertainties. Even more fundamental is the epistemological uncer-
tainty attributed to different social costs. As a result, the range of plau-
sible social costs and benefits can be large. For example, the social
costs of the co-dimensions congestion, air pollution, accidents, and
noise in Beijing were assessed to equate to between 7.5 % to 15 %
of GDP (Creutzig and He, 2009). Improving energy security, mobility
access, traffic congestion, public health, and safety are all important
policy objectives that can possibly be influenced by mitigation actions
(Jacobsen, 2003; Goodwin, 2004; Hultkrantz etal., 2006; Rojas-Rueda
etal., 2011).
Energy security. Transport stands out in comparison to other energy
end-use sectors due to its almost complete dependence on petroleum
products (Sorrell and Speirs, 2009; Cherp etal., 2012). Thus, the sector
suffers from both low resilience of energy supply and, in many coun-
tries, low sufficiency of domestic resources. (For a broader discussion
on these types of concerns see Section 6.6.2.2). The sector is likely to
continue to be dominated by oil for one or more decades (Costan-
tini etal., 2007). For oil-importing countries, the exposure to volatile
and unpredictable oil prices affects the terms of trade and their eco-
nomic stability. Measuring oil independence is possible by measuring
the economic impact of energy imports (Greene, 2010b). Mitigation
strategies for transport (such as electrifying the sector and switching
to biofuels) would decrease the sector’s dependence on oil and diver-
sify the energy supply, thus increasing resilience (Leiby, 2007; Shakya
and Shrestha, 2011; Jewell etal., 2013). However, a shift away from oil
could have implications for energy exporters (see Chapter 14). Addi-
tionally, mitigation measures targeted at reducing the overall transport
demand — such as more compact urban form with improved transport
infrastructure and journey distance reduction and avoidance (see Sec-
tions 8.4 and 12.4.2.1) — may reduce exposure to oil price volatility
and shocks (Sovacool and Brown, 2010; Leung, 2011; Cherp et al.,
2012).
Access and mobility. Mitigation strategies that foster multi-modality
are likely to foster improved access to transport services particularly for
the poorest and most vulnerable members of society. Improved mobil-
ity usually helps provide access to jobs, markets, and facilities such as
hospitals and schools (Banister, 2011b; Boschmann, 2011; Sietchip-
ing etal., 2012). More efficient transport and modal choice not only
increases access and mobility it also positively affects transport costs
for businesses and individuals (Banister, 2011b). Transport systems that
are affordable and accessible foster productivity and social inclusion
(Banister, 2008; Miranda and Rodrigues da Silva, 2012).
Employment impact. In addition to improved access in developing
countries, a substantial number of people are employed in the formal
and informal public transport sector (UN-Habitat, 2013). A shift to pub-
lic transport modes is likely to generate additional employment oppor-
tunities in this sector (Santos etal., 2010). However, the net effect on
employment of a shift towards low-carbon transport remains unclear
(UNEP, 2011).
Traffic congestion. Congestion is an important aspect for decision
makers, in particular at the local level, as it negatively affects journey
times and creates substantial economic cost (Goodwin, 2004; Duranton
and Turner, 2011). For example, in the United States in 2000, time lost
in traffic amounted to around 0.7 % of GDP (Federal Highway Admin-
istration, 2000) or approximately 85 billion USD
2010
. This increased to
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8
Chapter 8
101 billion USD
2010
in 2010, also being 0.7 % of GDP, but with more
accurate data covering the cost per kilometre travelled of each major
vehicle type for 500 urban centres (Schrank etal., 2011). Time lost was
valued at 1.2 % of GDP in the UK (Goodwin, 2004); 3.4 % in Dakar,
Senegal; 4 % in Manila, Philippines (Carisma and Lowder, 2007); 3.3 %
to 5.3 % in Beijing, China (Creutzig and He, 2009); 1 % to 6 % in Bang-
kok, Thailand (World Bank, 2002) and up to 10 % in Lima, Peru where
people on average spend around four hours in daily travel (JICA, 2005;
Kunieda and Gauthier, 2007).
Modal shifts that reduce traffic congestion can simultaneously reduce
GHG emissions and short-lived climate forcers. These include road con-
gestion pricing, modal shifts from aviation to rail, and shifts from LDVs
to public transport, walking, and cycling (Cuenot etal., 2012). How-
ever, some actions that seek to reduce congestion can induce addi-
tional travel demand, for example, expansions of airport infrastructure
or construction of roads to increase capacity (Goodwin, 2004; ECMT,
2007; Small and van Dender, 2007).
Health. Exposure to vehicle exhaust emissions can cause cardiovas-
cular, pulmonary, and respiratory diseases and several other negative
health impacts (McCubbin, D. R., Delucchi, 1999; Medley etal., 2002;
Chapters 7.9.2, 8.2, and WG II Chapter 11.9). In Beijing, for example,
the social costs of air pollution were estimated to be as high as those
for time delays from congestion (Creutzig and He, 2009). Various strat-
egies to reduce fuel carbon intensity have varying implications for the
many different air pollutants. For example, many studies indicate lower
carbon monoxide and hydrocarbon emissions from the displacement of
fossil-based transport fuels with biofuels, but NO
x
emissions are often
higher. Advanced biofuels are expected to improve performance, such
as the low particulate matter emissions from ligno-cellulosic ethanol
(see Hill etal., 2009, Sathaye etal., 2011 and Section 11.13.5). Strat-
egies that target local air pollution, for example switching to elec-
tric vehicles, have the potential to also reduce CO2 emissions (Yedla
etal., 2005) and black carbon emissions (UNEP and WMO, 2011) pro-
vided the electricity is sourced from low-carbon sources. Strategies
to improve energy efficiency in the LDV fleet though fostering diesel-
powered vehicles may affect air quality negatively (Kirchstetter etal.,
2008; Schipper and Fulton, 2012) if not accompanied by regulatory
measures to ensure emission standards remain stable. The structure
and design of these strategies ultimately decides if this potential can
be realized (see Section 8.2).
Transport also contributes to noise and vibration issues, which affect
human health negatively (WHO, 2009; Oltean-Dumbrava etal., 2013;
Velasco etal., 2013). Transport-related human inactivity has also been
linked to several chronic diseases (WHO, 2008). An increase in walk-
ing and cycling activities could therefore lead to health benefits but
conversely may also lead to an increase in traffic accidents and a
larger lung intake of air pollutants (Kahn Ribeiro etal., 2012; Takeshita,
2012). Overall, the benefits of walking and cycling significantly out-
weigh the risks due to pollution inhalation (Rojas-Rueda etal., 2011;
Rabl and de Nazelle, 2012).
Assessing the social cost of public health is a contested area when
presented as disability-adjusted life years (DALYs). A reduction in
CO
2
emissions through an increase in active travel and less use of
ICE vehicles gave associated health benefits in London (7,332 DALYs
per million population per year) and Delhi (12,516 (DALYs / million
capita) / yr) — significantly more than from the increased use of lower-
emission vehicles (160 (DALYs / million capita) / yr) in London, and 1,696
in Delhi) (Woodcock etal., 2009). More generally, it has been found
consistently across studies and methods that public health benefits
(induced by modal shift from LDVs to non-motorized transport) from
physical activity outweighs those from improved air quality (Woodcock
etal., 2009; de Hartog etal., 2010; Rojas-Rueda etal., 2011; Grabow
etal., 2012; Maizlish etal., 2013). In a similar trend, reduced car use in
Australian cities has been shown to reduce health costs and improve
productivity due to an increase in walking (Trubka etal., 2010a).
Safety� The increase in motorized road traffic in most countries places
an increasing incidence of accidents with 1.27 million people killed
globally each year, of which 91 % occur in low and middle-income
countries (WHO, 2011). A further 20 to 50 million people suffer serious
injuries (WHO, 2011). By 2030, it is estimated that road traffic injuries
will constitute the fifth biggest reason for premature deaths (WHO,
2008). Measures to increase the efficiency of the vehicle fleet can also
positively affect the crash-worthiness of vehicles if more stringent
safety standards are adopted along with improved efficiency standards
(Santos etal., 2010). Lack of access to safe walking, cycling, and pub-
lic transport infrastructure remains an important element affecting the
success of modal shift strategies, in particular in developing countries
(Sonkin etal., 2006; Tiwari and Jain, 2012).
Fossil fuel displacement. Economists have criticized the assump-
tion that each unit of energy replaces an energy-equivalent quantity of
fossil energy, leaving total fuel use unaffected (Drabik and de Gorter,
2011; Rajagopal et al., 2011; Thompson etal., 2011). As with other
energy sources, increasing energy supply through the production of
bioenergy affects energy prices and demand for energy services, and
these changes in consumption also affect net global GHG emissions
(Hochman et al., 2010; Rajagopal et al., 2011; Chen and Khanna,
2012). The magnitude of the effect of increased biofuel production
on global fuel consumption is uncertain (Thompson etal., 2011) and
depends on how the world responds in the long term to reduced
petroleum demand in regions using increased quantities of biofu-
els. This in turn depends on the Organization of Petroleum Export-
ing Countries’ (OPEC) supply response and with China’s and India’s
demand response to a given reduction in the demand for petroleum
in regions promoting biofuels, and the relative prices of biofuels and
fossil fuels including from hydraulic fracturing (fracking) (Gehlhar
etal., 2010; Hochman etal., 2010; Thompson etal., 2011). Notably,
if the percentage difference in GHG emissions between an alternative
fuel and the incumbent fossil fuel is less than the percentage rebound
effect (the fraction not displaced, in terms of GHG emissions), a net
increase in GHG emissions will result from promoting the alternative
fuel, despite its nominally lower rating (Drabik and de Gorter, 2011).
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Table 8�4 | Overview of potential co-benefits (green arrows) and adverse side effects (orange arrows) of the main mitigation measures in the transport sector. Arrows pointing
up / down denote positive / negative effect on the respective objective / concern; a question mark (?) denotes an uncertain net effect. Co-benefits and adverse side-effects depend on
local circumstances as well as on the implementation practice, pace, and scale (see Section 6.6). For an assessment of macroeconomic, cross-sectoral effects associated with mitiga-
tion policies (e. g., energy prices, consumption, growth, and trade), see Sections 3.9, 6.3.6, 13.2.2.3 and 14.4.2. For possible upstream effects of low-carbon electricity and biomass
supply, see Sections 7.9 as well as 11.7 and 11.13.6. Numbers in brackets correspond to references below the table.
Mitigation measures
Effect on additional objectives / concerns
Economic Social (including health) Environmental
Reduction of fuel
carbon intensity:
electricity,
hydrogen, CNG,
biofuels, and other
fuels
↑
↑
Energy security (diversification, reduced oil
dependence and exposure to oil price volatility)
(1 – 3,32 – 34,94)
Technological spillovers (e. g., battery
technologies for consumer electronics)
(17,18,44,55,90)
?
↓
↑
↓
↓
Health impact via urban air pollution (59,69) by
CNG, biofuels: net effect unclear
(13,14,19,20,36,50)
Electricity, hydrogen: reducing most
pollutants (13,20,21,36,58,63,92)
Shift to diesel: potentially increasing
pollution (11,23,25)
Health impact via reduced noise (electricity and
fuel cell LDVs) (10,61,64 – 66,82)
Road safety (silent electric LDVs at low speed)
(56)
↓
↑
?
Ecosystem impact of electricity and hydrogen
via:
Urban air pollution (13,20,69,91 – 93)
Material use (unsustainable resource mining)
(17,18)
Ecosystem impact of biofuels (24,41,42,89)
Reduction of energy
intensity
↑
Energy security (reduced oil dependence and
exposure to oil price volatility) (1 – 3,32 – 34)
↓
↑
Health impact via reduced urban air pollution
(22,25,43,59,62,69,84)
Road safety (crash-worthiness depending on the
design of the standards) (38,39,52,60)
↓
Ecosystem and biodiversity impact via reduced
urban air pollution (20,22,69,95)
Compact urban
form and improved
transport
infrastructure
Modal shift
↑
↑
?
Energy security (reduced oil dependence and
exposure to oil price volatility) (77 – 80,86)
Productivity (reduced urban congestion and
travel times, affordable and accessible transport)
(6 – 8,26,35,45,46,48,49)
Employment opportunities in the public
transport sector vs. car manufacturing jobs
(38,76,89)
↓
↑
↓
↑
↑
Health impact for non-motorized modes via
Increased physical activity
(7,12,27,28,29,51,64,70,73,74)
Potentially higher exposure to air pollution
(19,27,59,69,70,74)
Noise (modal shift and travel reduction)
(58,61,64 – 66,81 – 83)
Equitable mobility access to employment
opportunities, particularly in developing
countries (4,5,8,9,26,43,47,49)
Road safety (via modal shift and / or
infrastructure for pedestrians and cyclists)
(12,27,37,39,40,87,88)
↓
↓
Ecosystem impact via
Urban air pollution (20,54,58,60,69)
Land-use competition (7,9,58,71,75)
Journey distance
reduction and
avoidance
↑
↑
Energy security (reduced oil dependence and
exposure to oil price volatility) (31,77 – 80,86)
Productivity (reduced urban congestion, travel
times, walking) (6 – 8,26,45,46,49)
↓
Health impact (for non-motorized transport
modes) (7,12,22,27 – 30,67,68,72,75)
↓
↑
↓
Ecosystem impact via
Urban air pollution (20,53,54,60,69)
New / shorter shipping routes (15,16,57)
Land-use competition from transport
infrastructure (7,9,58,71,75)
References: 1: Greene (2010b), 2: Costantini etal. (2007), 3: Bradley and Lefevre (2006), 4: Boschmann (2011), 5: Sietchiping etal. (2012), 6: Cuenot etal. (2012), 7: Creutzig
etal. (2012a), 8: Banister (2008), 9: Geurs and Van Wee (2004), Banister (2008), 10: Creutzig and He (2009), 11: Leinert etal. (2013), 12: Rojas-Rueda etal. (2011), 13: Sathaye
etal. (2011), 14: Hill etal. (2009), 15: Garneau etal. (2009), 16: Wassmann (2011), 17: Eliseeva and Bünzli (2011), 18: Massari and Ruberti (2013), 19: Takeshita (2012), 20:
Kahn Ribeiro etal. (2012), 21: IEA (2011a), 22: Woodcock etal. (2009), 23: Schipper and Fulton (2012), 24: see Section 11.13.6, 25: Kirchstetter etal. (2008), 26: Banister (2008),
Miranda and Rodrigues da Silva (2012), 27: Rojas-Rueda etal. (2011), Rabl and de Nazelle (2012), 28: Jacobsen (2003), 29: Hultkrantz etal. (2006), 30: Goodwin (2004), 31: Sor-
rell and Speirs (2009), 32: Jewell etal. (2013), 33: Shakya and Shrestha (2011), 34: Leiby (2007), 35: Duranton and Turner (2011), 36: Trubka etal. (2010a), 37: WHO (2011), 38:
Santos etal. (2010), 39: Tiwari and Jain (2012), 40: Sonkin etal. (2006), 41: Chum etal. (2011), 42: Larsen etal. (2009), 43: Steg and Gifford (2005), 44: Christensen etal. (2012),
45: Schrank etal. (2011), 46: Carisma and Lowder (2007), 47: World Bank (2002), 48: JICA (2005), 49: Kunieda and Gauthier (2007), 50: see Section 11.13.5, 51: Maizlish etal.
(2013), 52: WHO (2008), 53: ICCT (2012b), 54: Yedla etal. (2005), 55: Lu etal. (2013), 56: Schoon and Huijskens (2011), 57: see Section 8.5, 58: see Section 12.8, 59: Medey etal.
(2002), 60: Machado-Filho (2009), 61: Milner etal. (2012), 62: Kim Oanh etal. (2012), 63: Fulton etal. (2013), 64: de Nazelle etal. (2011), 65: Twardella and Ndrepepa (2011), 66:
Kawada (2011), 67: Grabow etal. (2012), 68: Pucher etal. (2010), 69: Section 7.9.2 and WGII Section 11.9, 70: de Hartog etal. (2010), 71: Heath etal. (2006), 72: Saelens etal.
(2003), 73: Sallis etal. (2009), 74: Hankey and Brauer (2012), 75: Cervero and Sullivan (2011), 76: Mikler (2010), 77: Cherp etal. (2012), 78: Leung (2011), 79: Knox-Hayes etal.
(2013), 80: Sovacool and Brown (2010), 81: WHO (2009), 82: Oltean-Dumbrava etal. (2013), 83: Velasco etal. (2013), 84: Smith etal. (2013), 86: see Section 8.4, 87: Schepers
etal. (2013), 88: White (2004), 89: UNEP / GEF (2013), 90: Rao and Wang (2011), 91: Notter etal. (2010), 92: Sioshansi and Denholm (2009), 93: Zackrisson etal. (2010), 94:
Michalek etal. (2011), 95: see Section 8.2.2.1.
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If biofuels displace high carbon-intensity oil from tar sands or heavy
oils, the displacement effect would provide higher GHG emission sav-
ings. Estimates of the magnitude of the petroleum rebound effect
cover a wide range and depend on modelling assumptions. Two recent
modelling studies suggest that biofuels replace about 30 – 70 % of the
energy equivalent quantity of petroleum-based fuel (Drabik and de
Gorter, 2011; Chen and Khanna, 2012), while others find replacement
can be as low as 12 – 15 % (Hochman etal., 2010). Under other circum-
stances, the rebound can be negative. The rebound effect is always
subject to the policy context, and can be specifically avoided by global
cap and pricing instruments.
8�7�2 Technical risks and uncertainties
Different de-carbonization strategies for transport have a number of
technological risks and uncertainties associated with them. Unsus-
tainable mining of resources to supply low-carbon transport technol-
ogies such as batteries and fuel cells may create adverse side effects
for the local environment (Massari and Ruberti, 2013; Eliseeva and
Bünzli, 2011). Mitigation options from lower energy-intensity tech-
nologies (e. g., electric buses) and reduced fuel carbon intensity (e. g.,
biofuels) are particularly uncertain regarding their technological via-
bility, sources of primary energy, and biomass and lifecycle emission
reduction potential (see Section 8.3). Biofuels indicators are being
developed to ensure a degree of sustainability in their production
and use (UNEP / GEF, 2013; Sections 11.13.6 and 11.13.7). For ship-
ping, there is potential for new and shorter routes such as across
the Arctic, but these may create risks to vulnerable ecosystems (see
Section 8.5).
A focus on improving vehicle fuel efficiency may reduce GHG emissions
and potentially improve air quality, but without an increase in modal
choice it may not result in improved access and mobility (Steg and Gif-
ford, 2005). The shift toward more efficient vehicles, for example the
increasing use of diesel for the LDV fleet in Europe, has also created
tradeoffs such as negatively affecting air quality in cities (Kirchstetter
etal., 2008). More generally, mitigation options are also likely to be
subject to rebound effects to varying degrees (see Sections 8.3 and
8.10).
8�7�3 Technological spillovers
Advancements in technologies developed for the transport sector may
have technological spillovers to other sectors. For example advance-
ments in battery technology systems for consumer electronics could
facilitate the development of batteries for electric vehicles and vice-
versa (Rao and Wang, 2011). The production of land-competitive biofu-
els can also have direct and indirect effects on biodiversity, water, and
food availability (see Sections 11.13.6 and 11.13.7). Other areas where
technological spillovers may occur include control and navigation sys-
tems and other information technology applications.
8.8 Barriers and opportunities
Barriers and opportunities are processes that hinder or facilitate deploy-
ment of new transport technologies and practices. Reducing transport
GHG emissions is inherently complex as increasing mobility with LDVs,
HDVs, and aircraft has been associated with increasing wealth for the
past century of industrialization (Meyer etal., 1965; Glaeser, 2011). The
first signs of decoupling fossil fuel-based mobility from wealth genera-
tion are appearing in OECD countries (Kenworthy, 2013). To decouple
and reduce GHG emissions, a range of technologies and practices have
been identified that are likely to be developed in the short- and long-
terms (see Section 8.3), but barriers to their deployment exist as do
opportunities for those nations, cities, and regions willing to make low-
carbon transport a priority. There are many barriers to implementing a
significantly lower carbon transport system, but these can be turned
into opportunities if sufficient consideration is given and best-practice
examples are followed.
8�8�1 Barriers and opportunities to reduce
GHGs by technologies and practices
The key transport-related technologies and practices garnered from
sections above are set out below in terms of their impact on fuel car-
bon intensity, improved energy intensity of technologies, system infra-
structure efficiency, and transport demand reduction. Each has short-
and long-term potentials to reduce transport GHG emissions that are
then assessed in terms of their barriers and opportunities (Table 8.5).
(Details of policies follow in Section 8.10).
Psychological barriers can impede behavioural choices that might oth-
erwise facilitate mitigation as well as adaptation and environmental
sustainability. Many individuals are engaged in ameliorative actions to
improve their local environment, although many could do more. Gif-
ford (2011) outlined barriers that included “limited cognition about
the problem, ideological worldviews that tend to preclude pro-envi-
ronmental attitudes and behaviour, comparisons with the responses of
other people, sunk costs and behavioural momentum, a dis-credence
toward experts and authorities, perceived risks as a result of making
change and positive but inadequate confidence to make behavioural
change.”
The range of barriers to the ready adoption of the above technolo-
gies and practices have been described in previous sections, but are
summarized in Table 8.5 along with the opportunities available. The
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challenges involved in removing barriers in each of the 16 elements
listed depend on the politics of a region. In most places, reducing fuel
carbon and energy intensities are likely to be relatively easy as they are
technology-based, though they can meet capital investment barriers
in developing regions and may be insufficient in the longer-term. On
the other hand, system infrastructure efficiency and transport demand
reduction options would require human interventions and social
change as well as public investment. Although these may not require
as much capital investment, they would still require public acceptance
of any transport policy option (see Section 8.10). As implementation
approaches, public acceptance fluctuates, so political support may be
required at critical times (Pridmore and Miola, 2011).
Table 8�5 | Transport technologies and practices with potential for both short- and long-term GHG reduction and the related barriers and opportunities in terms of the policy arenas
of fuel carbon intensity, energy intensity, infrastructure, and activity.
Transport technology or
practice
Short-term possibilities Long-term possibilities Barriers Opportunities References
Fuel carbon intensity: fuel switching BEV — Battery electric vehicle; PHEV — Plug-in hybrid electric vehicle; FCV — Fuel cell vehicles; CHP — combined heat and power;
CNG — Compressed natural gas; LNG — Liquefied natural gas; CBG — Compressed biogas; LBG — Liquefied biogas)
1. BEVs and PHEVs based
on renewable electricity.
Rapid increase in use likely
over next decade from a small
base, so only a small impact
likely in short-term.
Significant replacement of
ICE-powered LDVs.
EV and battery costs reducing
but still high.
Lack of infrastructure, and
recharging standards not
uniform.
Vehicle range anxiety.
Lack of capital and electricity
in some least developed
countries.
Universal standards
adopted for EV rechargers.
Demonstration in green
city areas with plug-in
infrastructure.
Decarbonized electricity.
Smart grids based on
renewables.
EV subsidies.
New business models, such as
community car sharing.
EPRI 2008; Beck ,2009; IEA,
2011; Salter etal., 2011;
Kley etal., 2011; Leurent &
Windisch, 2011; Graham-
Rowe etal., 2012
2. CNG, LNG, CBG and LBG
displacing gasoline in
LDVs and diesel in HDVs.
Infrastructure available in
some cities so can allow
a quick ramp – up of gas
vehicles in these cities.
Significant replacement of
HDV diesel use depends on
ease of engine conversion,
fuel prices and extent of
infrastructure.
Insufficient government
programmes, conversion
subsidies and local gas
infrastructure and markets.
Leakage of gas.
Demonstration gas conversion
programmes that show cost
and health co-benefits. Fixing
gas leakage in general.
IEA, 2007; Salter etal., 2011;
Alvarez etal., 2012
3. Biofuels displacing
gasoline, diesel and
aviation fuel.
Niche markets continue for
first generation biofuels (3 %
of liquid fuel market, small
biogas niche markets).
Advanced and drop-in
biofuels likely to be adopted
around 2020 – 2030, mainly
for aviation.
Some biofuels can be
relatively expensive,
environmentally poor and
cause inequalities by inducing
increases in food prices.
Drop-in fuels attractive for all
vehicles.
Biofuels and bio-electricity
can be produced together,
e. g., sugarcane ethanol and
CHP from bagasse.
New biofuel options need to
be further tested, particularly
for aviation applications.
Ogden etal., 2004; Fargione
etal., 2010; IEA, 2010; Plevin
etal., 2010; Creutzig etal.,
2011; Salter etal., 2011;
Pacca and Moreira, 2011;
Flannery etal., 2012
Energy intensity: efficiency of technologies FEV — fuel efficient vehicles ICE — internal combustion engine
4. Improved vehicle ICE
technologies and
on-board information
and communication
technologies (ICT) in fuel-
efficient vehicles.
Continuing fuel efficiency
improvements across new
vehicles of all types can show
large, low-cost, near-term
reductions in fuel demand.
Likely to be a significant
source of reduction.
Behavioural issues (e. g.,
rebound effect). Consumer
choices can reduce vehicle
efficiency gains.
Insufficient regulatory
support for vehicle emissions
standards.
On-road performance
deteriorates compared with
laboratory tests.
Creative regulations that
enable quick changes to
occur without excessive costs
on emissions standards. China
and most OECD countries
have implemented standards.
Reduced registration tax
can be implemented for low
CO
2
eq-based vehicles.
Schipper etal., 2000; Ogden
etal., 2004; Small and van
Dender, 2007; Sperling and
Gordon, 2009; Timilsina and
Dulal, 2009; Fuglestvedt etal.,
2009; Mikler, 2010; Salter
etal., 2011
Structure: system infrastructure efficiency
5. Modal shift by public
transport displacing
private motor vehicle use.
Rapid short-term growth
already happening.
Significant displacement
only where quality system
infrastructure and services are
provided.
Availability of rail, bus, ferry,
and other quality transit
options.
Density of people to allow
more access to services.
Levels of services.
Time barriers on roads
without right of way
Public perceptions.
Investment in quality transit
infrastructure, density of
adjacent land use, and
high level of services using
innovative financing that
builds in these features.
Multiple co-benefits especially
where walkability health
benefits are a focus.
Kenworthy, 2008; Millard-Ball
& Schipper, 2011; Newman
and Kenworthy, 2011; Salter
etal., 2011; Buehler and
Pucher, 2011; Newman and
Matan, 2013
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Transport technology or
practice
Short-term possibilities Long-term possibilities Barriers Opportunities References
6. Modal shift by cycling
displacing private motor
vehicle use.
Rapid short-term growth
already happening in many
cities.
Significant displacement
only where quality system
infrastructure is provided.
Cultural barriers and lack of
safe cycling infrastructure and
regulations. Harsh climate.
Demonstrations of quality
cycling infrastructure
including cultural programmes
and bike-sharing schemes.
Bassett etal., 2008; Garrard
etal., 2008; Salter etal.,
2011; Anon, 2012; Sugiyama
etal., 2012
7. Modal shift by walking
displacing private motor
vehicle use.
Some growth but depends on
urban planning and design
policies being implemented.
Significant displacement
where large-scale adoption of
polycentric city policies and
walkable urban designs are
implemented.
Planning and design policies
can work against walkability
of a city by too easily allowing
cars into walking city areas.
Lack of density and
integration with transit.
Culture of walkability.
Large-scale adoption of
polycentric city policies and
walkable urban designs
creating walking city in
historic centres and new ones.
Cultural programmes.
Gehl, 2011; Höjer etal., 2011;
Leather etal., 2011; Salter
etal., 2011
8. Urban planning by
reducing the distances to
travel within urban areas.
Immediate impacts where
dense transit-oriented
development (TOD) centres
are built.
Significant reductions where
widespread polycentric city
policies are implemented.
Urban development does
not always favour dense TOD
centres being built. TODs need
quality transit at their base.
Integration of professional
areas required.
Widespread polycentric city
policies implemented with
green TODs, backed by quality
transit. Multiple co-benefits
in sprawl costs avoided and
health gains.
Anon, 2004; Anon, 2009;
Naess, 2006; Ewing etal.,
2008; Cervero and Murakami,
2009; Cervero and Murakami,
2010; Cervero and Sullivan,
2011; Salter etal., 2011;
Lefèvre; 2009
9. Urban planning by
reducing private motor
vehicle use through
parking and traffic
restraint.
Immediate impacts on traffic
density observed.
Significant reductions only
where quality transport
alternatives are available.
Political barriers due to
perceived public opposition
to increased costs, traffic and
parking restrictions. Parking
codes too prescriptive for
areas suited to walking and
transit.
Demonstrations of better
transport outcomes from
combinations of traffic
restraint, parking and new
transit / walking infrastructure
investment.
Gwilliam, 2003; ADB, 2011;
Creutzig etal., 2011; Shoup,
2011; Newman and Matan,
2013
10. Modal shift by displacing
aircraft and LDV trips
through high-speed rail
alternatives.
Immediate impacts after
building rail infrastructure.
Continued growth but only
short-medium distance trips
suitable.
High-speed rail infrastructure
expensive.
Demonstrations of how to
build quality fast-rail using
innovative finance.
Park and Ha, 2006; Gilbert
and Perl, 2010; Åkerman,
2011; Salter etal., 2011
11. Modal shift of freight by
displacing HDV demand
with rail.
Suitable immediately for
medium- and long-distance
freight and port traffic.
Substantial displacement
only if large rail infrastructure
improvements made,
the external costs of
freight transport are fully
internalized, and the quality
of rail services are enhanced.
EU target to have 30 % of
freight tonne-km moving
more than 300 km to go by
rail (or water) by 2030.
Inadequacies in rail
infrastructure and service
quality. Much freight
moved over distances that
are too short for rail to be
competitive.
Upgrading of inter-modal
facilities. Electrification of rail
freight services. Worsening
traffic congestion on road
networks and higher fuel cost
will favour rail.
IEA, 2009; Schiller etal.,
2010; Salter etal., 2011
12. Modal shift by displacing
truck and car use through
waterborne transport.
Niche options already
available. EU “Motorways
of the Sea” programme
demonstrates potential to
expand short-sea shipping
share of freight market.
Potential to develop beyond
current niches, though will
require significant investment
in new vessels and port
facilities.
Lack of vision for water
transport options and land-
locked population centres.
Long transit times. Tightening
controls on dirty bunker fuel
and SO
x
and NO
x
emissions
raising cost and reducing
modal competitiveness.
Demonstrations of quality
waterborne transport that
can be faster and with
lower-carbon emissions than
alternatives.
Fuglestvedt etal., 2009;
Salter etal. 2011
13. System optimization by
improved road systems,
freight logistics and
efficiency at airports and
ports.
Continuing improvements
showing immediate impacts.
Insufficient in long term to
significantly reduce carbon
emissions without changing
mode, reducing mobility, or
reducing fuel carbon intensity.
Insufficient regulatory
support and key performance
indicators (KPIs) covering
logistics and efficiency.
Creative regulations and KPIs
that enable change to occur
rapidly without excessive
costs.
Pels and Verhoef, 2004;
A. Zhang and Y. Zhang,
2006; Fuglestvedt etal.,
2009; Kaluza etal., 2010;
McKinnon, 2010; Simaiakis
and Balakrishnan, 2010;
Salter etal., 2011
Activity: demand reduction
14. Mobility service
substitution by reducing
the need to travel
through enhanced
communications.
Niche markets growing and
ICT improving in quality and
reliability.
Significant reductions possible
after faster broadband and
quality images available,
though ICT may increase the
need for some trips.
Technological barriers due
to insufficient broadband in
some regions.
Demonstrations of improved
video-conferencing system
quality.
Golob and Regan, 2001;
Choo etal., 2005; Wang and
Law, 2007; Yi and Thomas,
2007; Zhen etal., 2009; Salter
etal., 2011; Mokhtarian and
Meenakshisundaram, 2002
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Transport technology or
practice
Short-term possibilities Long-term possibilities Barriers Opportunities References
15. Behavioural change from
reducing private motor
vehicle use through
pricing policies, e.g,
network charges and
parking fees.
Immediate impacts on traffic
density observed.
Significant reductions only
where quality transport
alternatives are available.
Political barriers due to
perceived public opposition to
increased pricing costs. Lack
of administrative integration
between transport, land-use
and environment departments
in city municipalities.
Demonstrations of better
transport outcomes from
combinations of pricing,
traffic restraint, parking
and new infrastructure
investment from the revenue.
Removing subsidies to fossil
fuels important for many
co-benefits.
Litman, 2005, 2006; Salter
etal., 2011; Creutzig etal.,
2012a
16. Behavioural change
resulting from education
to encourage gaining
benefits of less motor
vehicle use.
Immediate impacts of
10 – 15 % reduction of LDV
use are possible.
Significant reductions only
where quality transport
alternatives are available.
Lack of belief by politicians
and professionals in the value
of educational behaviour
change programmes.
Demonstrations of ‘travel
smart’ programmes linked to
improvements in sustainable
transport infrastructure.
Cost effective and multiple
co-benefits.
Pandey, 2006; Goodwin and
Lyons, 2010; Taylor and Philp,
2010; Ashton-Graham etal.,
2011; Höjer etal., 2011;
Salter etal., 2011
8�8�2 Financing low-carbon transport
Transport is a foundation for any economy as it enables people to
be linked, goods to be exchanged, and cities to be structured (Glae-
ser, 2011). Transport is critical for poverty reduction and growth in
the plans of most regions, nations, and cities. It therefore is a key
area to receive development funding. In past decades the amount of
funding going to transport through various low-carbon mechanisms
had been relatively low, but has had a recent increase. The projects
registered in the United Nations Environmental Programme (UNEP)
pipeline database for the clean development mechanism (CDM)
shows only 42 projects out of 6707 were transport-related (Kopp,
2012). The Global Environment Facility (GEF) has approved only 28
projects in 20 years, and the World Bank’s Clean Technology Fund
has funded transport projects for less than 17 % of the total. If this
international funding does not improve, then transport could move
from emitting 22 % of energy-related GHGs in 2009 to reach 80 %
by 2050 (ADB, 2012a). Conversely, national appropriate mitigation
measures (NAMAs) could attract low-carbon financing in the trans-
port area for the developing world. To support sustainable transport
system development, eight multi-lateral development banks have
pledged to invest around 170 billion USD
2010
over the next ten years
(Marton-Lefèvre, 2012).
A major part of funding sustainable transport could arise from the redi-
rection of funding from unsustainable transport (Sakamoto etal., 2010;
UNEP, 2011; ADB, 2012b). In addition, land-based taxes or fees can
capitalize on the value gains brought by sustainable transport infra-
structures (Chapter 12.5.2). For example, in locations close to a new rail
system, revenue can be generated from land-based taxes and council
rates levied on buildings that are seen to rise by 20 – 50 % compared to
areas not adjacent to such an accessible facility (Cervero 1994; Haider
and Miller, 2000; Rybeck, 2004). Local municipal financing by land
value capture and land taxes could be a primary source of financing
for public transit and non-motorized transport infrastructure, especially
in rapidly urbanizing Asia (Chapter 12.5.2; Bongardt etal., 2013). For
example, a number of value capture projects are underway as part of
the rapid growth in urban rail systems, including Indian cities (Newman
etal., 2013). The ability to fully outline the costs and benefits of low-
carbon transport projects will be critical to accessing these new fund-
ing opportunities. R&D barriers and opportunities exist for all of these
agendas in transport.
8�8�3 Institutional, cultural, and legal barriers
and opportunities
Institutional barriers to low-carbon transport include international
standards required for new EV infrastructure to enable recharging;
low pricing of parking; lack of educational programmes for modal
shift; and polycentric planning policies that require the necessary insti-
tutional structures (OECD, 2012; Salter etal., 2011). Cultural barriers
underlie every aspect of transport, for example, automobile depen-
dence being built into a culture and legal barriers that can exist to pre-
vent the building of dense, mixed-use community centres that reduce
car dependence. Overall, there are political barriers that combine most
of the above (Pridmore and Miola, 2011).
Opportunities also exist. Low-carbon transport elements in green
growth programmes (OECD, 2011; Hargroves and Smith, 2008) are
likely to be the basis of changing economies because they shape cit-
ies and create wealth (Glaeser, 2011; Newman et al., 2009). Those
nations, cities, businesses, and communities that grasp the opportuni-
ties to demonstrate these changes are likely to be the ones that benefit
most in the future (OECD, 2012). The process of decoupling economic
growth from fossil fuel dependence could become a major feature of
the future economy (ADB, 2012a) with sustainable transport being one
of four key approaches. Overcoming the barriers to each technology
and practice (Table 8.5) could enable each to contribute to a more
sustainable transport system and realize the opportunities from tech-
nological and social changes when moving towards a decarbonized
economy of the future.
637637
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8.9 Sectoral implications
of transformation
pathways and sustainable
development
Scenarios that focus on possible reductions of energy use and CO
2
emissions from transport are sourced from either integrated models
that incorporate a cross-sector approach to modelling global emissions
reductions and other mitigation options, or sectoral models that focus
solely on transport and its specific potential for emissions reductions.
A comparison of scenarios from both integrated and sectoral models
with a focus on long-term concentration goals up until 2100 is con-
ducted in this section. This comparison is complemented by the results
of the transport-specific evaluation of cost and potentials in Section
8.6 and supported by a broader integrated assessment in Chapter 6
7
.
The integrated and sectoral model transport literature presents a wide
range of future CO
2
emissions reduction scenarios and offers two
distinct forms of assessment. Both contemplate how changes in pas-
senger and freight activity, structure, energy intensity, and fuel carbon
intensity could each contribute to emissions reductions and assist the
achievement of concentration goals.
The integrated model literature focuses upon systemic assess-
ments of the impacts of macro-economic policies (such as limits on
global / regional emissions or the implementation of a carbon tax) and
reviews the relative contributions of a range of sectors to overall global
mitigation efforts (Section 6.2.1). Within the WG III AR5 Scenario Data-
base (Annex II.10), transport specific variables are not available for
all scenarios. Therefore, the present analysis is based on a sub-sample
of almost 600 scenarios
8
. Due to the macro-economic scale of their
analysis, integrated models have a limited ability to assess behaviour
changes that may result from structural developments impacting on
7
Section 6.2.2 and Annex II.10 provide details on the WG III AR5 Scenario Data-
base, which is the source of more than 1,200 integrated scenarios.
8
This section builds upon the scenarios which were collated by Chapter 6 in the
WG III AR5 Scenario Database and compares them to global scale transport
studies. The scenarios were grouped into baseline and mitigation scenarios.
As described in more detail in Chapter 6.3.2, the scenarios are further catego-
rized into bins based on 2100 concentrations: between 430 – 480 ppm CO
2
eq,
480 – 530 ppm CO
2
eq, 530 – 580 ppm CO
2
eq, 580 – 650 ppm CO
2
eq, 650 – 720 ppm
CO
2
eq, and >720 ppm CO
2
eq. An assessment of geo-physical climate uncer-
tainties, consistent with the dynamics of Earth System Models assessed in WGI,
found that the most stringent of these scenarios, leading to 2100 concentrations
between 430 and 480 ppm CO
2
eq, would lead to an end-of-century median
temperature change between 1.6 to 1.8 °C compared to pre-industrial times,
although uncertainties in understanding of the climate system mean that the
possible temperature range is much wider than this. They were found to maintain
temperature change below 2 °C over the course of the century with a likely
chance. Scenarios in the concentration category of 650 – 720 ppm CO
2
eq cor-
respond to comparatively modest mitigation efforts, and were found to lead to
median temperature rise of approximately 2.6 – 2.9 °C in 2100 (Chapter 6.3.2).
The x-axis of Figures 8.9 to 8.12 show specific sample numbers for each category
of scenario reviewed.
modal shift or journey avoidance, behavioural factors such as travel
time and budget might contribute up to 50 % reduction of activity
globally in 2100 compared to the 2005 baseline (Girod etal., 2013).
Sectoral scenarios, however, are able to integrate results concerning
emission reduction potentials from sector specific interventions (such
as vehicle taxation, parking fees, fuel economy standards, promotion
of modal shift, etc.). They can be instrumental in evaluating how poli-
cies that target structural factors
9
can impact on passenger and freight
travel demand reductions (see Sections 8.4 and 8.10). Unlike inte-
grated models, sectoral studies do not attempt to measure transport
emissions reductions with respect to the amounts that other sectors
could contribute in order to reach long-term concentration goals.
8�9�1 Long term stabilization goals — integra-
ted and sectoral perspectives
A diversity of transformation pathways highlights the possible range of
decarbonization options for transport (Section 6.8). Results from both
integrated and sectoral models up until 2050 closely match each other.
Projected GHG emissions vary greatly in the long term integrated sce-
narios, reflecting a wide range in assumptions explored such as future
population, economic growth, policies, technology development, and
acceptance (Section 6.2.3). Without policy interventions, a continua-
tion of current travel demand trends could lead to a more than dou-
bling of transport-related CO
2
emissions by 2050 and more than a
tripling by 2100 in the highest scenario projections (Figure 8.9). The
convergence of results between integrated and sectoral model studies
suggests that through substantial, sustained, and directed policy inter-
ventions, transport emissions can be consistent with limiting long-term
concentrations to 430 – 530 ppm CO
2
eq.
The growth of global transport demand could pose a significant chal-
lenge to the achievement of potential emission reduction goals. The
average transport demand growth from integrated scenarios with
respect to 2010 levels suggests that total passenger and freight travel
will continue to grow in the coming decades up to 2050, with most
of this growth taking place within developing country regions where
large shares of future population and income growth are expected
(Figure 8.10) (UN Secretariat, 2007).
A positive income elasticity and the relative price-inelastic nature
of passenger travel partially explain the strength of the relationship
between travel and income (Dargay, 2007; Barla etal., 2009). Both
integrated and sectoral model projections for total travel demand
show that while demand in non-OECD countries grows rapidly, a lower
starting point results in a much lower per capita level of passenger
travel in 2050 than in OECD countries (Figure 8.10) (IEA, 2009; Fulton
9
These include land use planning that favours high density or polycentric urban
forms; public transport oriented developments with mixed uses; and high quality
city environments.
638638
Transport
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Chapter 8
<Beginpic>
Figure 8�9 | Direct global transport CO
2
emissions. All results for passenger and freight transport are indexed relative to 2010 values for each scenario from integrated models
grouped by CO
2
eq concentration levels by 2100, and sectoral studies grouped by baseline and policy categories. Sources: Integrated models — WG III AR5 Scenario Database
(AnnexII.10). Sectoral models: IEA (2008, 2011b, 2012b), WEC (2011a), EIA (2011), IEEJ (2011).
Note: All figures in Section 8.9 show the full range of results for both integrated and sectoral studies. Where the data is sourced from the WG III AR5 Scenario Database a line
denotes the median scenario and a box and bolder colours highlight the inter-quartile range. The specific observations from sectoral studies are shown as black dots with light bars
(policy) or dark bars (baseline) to give the full ranges. “n” equals number of scenarios assessed in each category.
n=
166 513193233 166 513193233 166 411193233 161 163198
430-530 ppm CO
2
eq
>650 ppm CO
2
eq
Policy
530-650 ppm CO
2
eq
Baseline
Units in Comparison to 2010 [2010 = 1]
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
2100205020302020
IAM Sectoral IAM Sectoral SectoralIAM IAM
Min
75
th
Percentile
Max
Median
25
th
Percentile
Min
Max
Figure 8�10 | Global passenger (p-km / capita / yr) and freight (t-km / capita / yr) regional demand projections out to 2050 based on integrated models for various CO
2
eq concentra-
tion levels by 2100 — with normalized values highlighting growth and controlling differences in base year values across models. Source: WG III AR5 Scenario Database (Annex II.10).
0
5000
30,000
10,000
15,000
20,000
25,000
0
1.0
1.5
2.0
2.5
3.0
4.5
4.0
3.5
2040 20502020 20302040
Relative to 2010 Values
FreightPassengersFreightPassengers
Absolute Values
20502020 2030
2040 20502020 20302040 20502020 2030
Transport Demand for Passengers [p-km/cap/yr] and Freight [t-km/cap/yr]
Transport Demand Relative to 2010 (Index 2010 = 1)
Global
LAM
MAF
ASIA
EIT
OECD-1990
530-650
ppm CO
2
eq
430-530
ppm CO
2
eq
639639
Transport
8
Chapter 8
etal., 2013). Consistent with a recent decline in growth of LDV use
in some OECD countries (Goodwin and Van Dender, 2013), integrated
and sectoral model studies have suggested that decoupling of passen-
ger transport from GDP could take place after 2035 (IEA, 2012; Girod
etal., 2012). However, with both transport demand and GDP tied to
population growth, decoupling may not be fully completed. At higher
incomes, substitution to faster travel modes, such as fast-rail and air
travel, explains why total passenger and freight travel continues to rise
faster than per capita LDV travel (Schäfer etal., 2009).
Freight transport increases in all scenarios at a slower pace than pas-
senger transport, but still rises as much as threefold by 2050 in com-
parison to 2010 levels. Freight demand has historically been closely
coupled to GDP, but there is potential for future decoupling. Over the
long term, changes in activity growth rates (with respect to 2010) for
430 – 530 ppm CO
2
eq scenarios from integrated models suggest that
decoupling freight transport demand from GDP can take place earlier
than for passenger travel. Modest decreases in freight activity per dol-
lar of GDP suggest that a degree of relative decoupling between freight
and income has been occurring across developed countries includ-
ing Finland (Tapio, 2005), the UK (McKinnon, 2007a) and Denmark
(Kveiborg and Fosgerau, 2007). Two notable exceptions are Spain and
South Korea, which are at relatively later stages of economic develop-
ment (Eom etal., 2012). Where decoupling has occurred, it is partly
associated with the migration of economic activity to other countries
(Corbertt and Winebrake, 2008; Corbertt and Winebrake, 2011). See
Sections 3.9.5 and 5.4.1 for a broader discussion of leakage. Opportu-
nities for decoupling could result from a range of changes, including a
return to more localized sourcing (McKinnon, 2007b); a major shift in
the pattern of consumption to services and products of higher value;
the digitization of media and entertainment; and an extensive appli-
cation of new transport-reducing manufacturing technologies such as
3-D printing (Birtchnell etal., 2013).
Due to the increases in total transport demand, fuel consumption also
increases over time, but with GHG emissions at a lower level if policies
toward decarbonization of fuels and reduced energy intensity of vehi-
cles are successfully implemented. The integrated scenarios suggest
that energy intensity reductions for both passenger and freight trans-
port could continue to occur if the present level of fuel economy stan-
dards are sustained over time, or could decrease further with more
stringent concentration goals (Figure 8.11).
Projected reductions in energy intensity for freight transport scenarios
(EJ / bn t-km) in the scenarios show a wider spread (large ranges in
Figure 8.11 between the 25th and 75th percentiles) than for passen-
gers, but still tend to materialize over time. Aviation and road transport
have higher energy intensities than rail and waterborne transport (Fig-
ure 8.6). Therefore, they account for a larger share of emissions than
their share of meeting service demands (Girod etal., 2013). However,
limited data availability makes the assessment of changes in modal
structure challenging as not all integrated models provide information
at a sufficiently disaggregated level or fully represent structural and
behavioural choices. Sectoral studies suggest that achieving signifi-
cant reductions in aviation emissions will require reductions in the rate
of growth of travel activity through demand management alongside
technological advances (Bows etal., 2009).
In addition to energy intensity reductions, fuel carbon intensity can be
reduced further in stringent mitigation scenarios and play an important
role in the medium term with the potential for continued improvement
throughout the century (Figure 8.11). Scenarios suggest that fuel switch-
Figure 8�11 | Normalized energy intensity scenarios (indexed relative to 2010 values) out to 2100 for passenger (left panel) and freight transport (centre panel), and for fuel car-
bon intensity based on scenarios from integrated models grouped by CO
2
eq concentration levels by 2100 (right panel). Source: WG III AR5 Scenario Database (Annex II.10). Note
“n” equals number of scenarios assessed in each category.
Units in Comparison to 2010 [2010 = 1]
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Passenger [GJ/p-km] Freight [GJ/t-km] Fuel Carbon Intensity [tCO
2
/TJ]
n=
80 9180917491 83748074 66 70768580 76 7085 76 7085 76 6277 188164228 164 188228 164 188228 161 163198
2020 2030 2050 2100 210020302020 2050 210020302020 2050
430-530 ppm CO
2
eq
>650 ppm CO
2
eq
530-650 ppm CO
2
eq
Min
75
th
Percentile
Max
Median
25
th
Percentile
640640
Transport
8
Chapter 8
ing does not occur to a great extent until after 2020 – 2030 (Fig 8.12)
after which it occurs sooner in more stringent concentration scenarios.
The mix of fuels and technologies is difficult to foresee in the long term,
especially for road transport, but liquid petroleum fuels tend to domi-
nate at least up until 2050 even in the most stringent mitigation sce-
nario. Within some sectoral studies, assumed breakthroughs in biofuels,
fuel cell vehicles, and electrification of road vehicles help achieve deep
reductions in emissions by 2050 (Kahn Ribeiro et al., 2012; Williams
etal., 2012). Other studies are less confident about fuel carbon intensity
reductions, arguing that advanced biofuels, low-carbon electricity, and
hydrogen will all require time to make substantial contributions to miti-
gation efforts. They therefore attribute greater potential for emission
reductions to structural and behavioural changes (Salter etal., 2011).
Model assumptions for future technology cost, performance, regula-
tory environment, consumer choice, and fuel prices result in differ-
ent shares of fuels that could replace fossil fuels (Table 8.3; Krey and
Clarke, 2011). Availability of carbon dioxide capture and storage (CCS)
is also likely to have major impact on fuel choices (Luckow etal., 2010;
Sathaye etal., 2011). Uncertainty is evident by the wide ranges in all
the pathways considered, and are larger after 2050 (Bastani et al.,
2012; Wang etal., 2012; Pietzcker etal., 2013). In terms of direct emis-
sions reductions, biofuels tend to have a more important role in the
period leading up to 2050. In general, integrated models have been
criticized as being optimistic on fuel substitution possibilities, spe-
cifically with respect to lifecycle emission assumptions and hence the
utilization of biofuels (Sections 8.3 and 11.A.4; Creutzig etal., 2012a;
Pietzcker et al., 2013). However, scenarios from integrated models
are consistent with sectoral scenarios with respect to fuel shares in
2050 (Figure 8.12). Within the integrated model scenarios, deeper
emissions reductions associated with lower CO
2
eq concentrations in
2100 are consistent with increasing market penetration of low-carbon
electricity and hydrogen in the latter part of the century. Uncertainties
as to which fuel becomes dominant, as well as on the role of energy
efficiency improvements and fuel savings, are relevant to the strin-
gent mitigation scenarios (van der Zwaan etal., 2013). Indeed, many
scenarios show no dominant transport fuel source in 2100, with the
median values for electricity and hydrogen sitting between a 22 – 25 %
share of final energy, even for scenarios consistent with limiting con-
centrations to 430 – 530 ppm CO
2
eq in 2100 (Figure 8.12).
Both the integrated and sectoral model literature present energy effi-
ciency measures as having the greatest promise and playing the larg-
est role for emission reductions in the short term (Skinner etal., 2010;
Harvey, 2012; IEA, 2009; McKinnon and Piecyk, 2009; Sorrell et al.,
2012). Since models typically assume limited cost reduction impacts, they
include slow transitions for new transport technologies to reach large
cumulative market shares. For example, a range of both sectoral and inte-
grated studies note that it will take over 15 – 20 years for either BEVs or
FCVs to become competitive with ICE vehicles (Baptista etal., 2010; Epp-
stein etal., 2011; IEA, 2011c; Girod etal., 2012; Girod etal., 2013; Bosetti
and Longden, 2013; van der Zwaan etal., 2013). Since integrated models
do not contain a detailed representation of infrastructural changes, their
results can be interpreted as a conservative estimate of possible changes
to vehicles, fuels, and modal choices (Pietzcker etal., 2013).
The sectoral literature presents a more positive view of transforma-
tional opportunities than do the integrated models (IEA, 2008, 2012b;
DOE / EIA, 2010; Kahn Ribeiro et al., 2012). Sectoral studies suggest
that up to 20 % of travel demand could be reduced by avoided jour-
neys or shifts to low-carbon modes (McCollum and Yang, 2009; Har-
vey, 2012; IEA, 2012d; Kahn Ribeiro et al., 2012; Anable etal., 2012;
<Beginpic>
Figure 8�12 | Global shares of final fuel energy in the transport sector in 2020, 2050, and 2100 based on integrated models grouped by CO
2
eq concentration levels by 2100 and
compared with sectoral models (grouped by baseline and policies) in 2050. Box plots show minimum / maximum, 25
th
/ 75
th
percentile and median. Source: Integrated models — WG
III AR5 Scenario Database (Annex II.10). Sectoral models — IEA, 2012; IEA, 2011b; IEA, 2008; WEC, 2011a; EIA, 2011 and IEEJ, 2011.
Note: Interpretation is similar to that for Figs. 8.9 and 8.10, except that the boxes between the 75th and 25th percentiles for integrated model results have different colours to
highlight the fuel type instead of GHG concentration categories. The specific observations from sectoral studies are shown as black dots
n=
66349615474451277445127
>650 ppm CO
2
eq530-650 ppm CO
2
eq430-530 ppm CO
2
eq >650 ppm CO
2
eq530-650 ppm CO
2
eq430-530 ppm CO
2
eq >650 ppm CO
2
eq530-650 ppm CO
2
eq430-530 ppm CO
2
eq
2020
20502050 2100
Baseline Policy
Hydrogen
Electricity
Gas
Biofuels
Oil
0
10
20
30
40
50
60
70
80
90
100
IAMSectoralIAM
Share of Final Energy [%]
641641
Transport
8
Chapter 8
Huo and Wang, 2012). They also estimate that urban form and infra-
structure changes can play decisive roles in mitigation, particularly in
urban areas where 70 % of the world’s population is projected to live
in 2050 (Chapter 8.4 and 12.4), although the estimated magnitude
varies between 5 % and 30 % (Ewing, 2007; Creutzig and He, 2009;
Echenique et al., 2012). Altogether, for urban transport, 20 – 50 %
reduction in GHG emissions is possible between 2010 and 2050 com-
pared to baseline urban development (Ewing, 2007; Eliasson, 2008;
Creutzig and He, 2009; Lefèvre, 2009; Woodcock etal., 2009; Ewing
and Cervero, 2010; Marshall, 2011; Echenique etal., 2012; Viguié and
Hallegatte, 2012; Salon etal., 2012; Creutzig etal., 2012a). Since the
lead time for infrastructure development is considerable (Short and
Kopp, 2005), such changes can only be made on decadal time scales.
Conversely, some developing countries with fast growing economies
have shown that rapid transformative processes in spatial develop-
ment and public transport infrastructure are possible. Further advances
may be gaining momentum with a number of significant initiatives for
reallocating public funding to sustainable and climate-friendly trans-
port (Bongardt etal., 2011; Wittneben etal., 2009; ADB, 2012; New-
man and Matan, 2013).
8�9�2 Sustainable development
Within all scenarios, the future contribution of emission reductions from
developing countries carries especially large uncertainties. The accel-
Box 8�1 | Transport and sustainable development in developing countries
Passenger and freight mobility are projected to double in devel-
oping countries by 2050 (IEA, 2012e). This increase will improve
access to markets, jobs, education, healthcare and other services
by providing opportunities to reduce poverty and increase equity
(Africa Union, 2009; Vasconcellos, 2011; United Nations Human
Settlements Programme, 2012). Well-designed and well-managed
transport infrastructure can also be vital for supporting trade and
competitiveness (United Nations Human Settlements Programme,
2012). Driven by urbanization, a rapid transition from slow non-
motorized transport modes to faster modes using 2- or 3- wheel-
ers, LDVs, buses, and light rail is expected to continue (Schäfer
etal., 2009; Kumar, 2011). In rural areas of Africa and South Asia,
the development of all-season, high-quality roads is becoming
a high priority (Africa Union, 2009; Arndt etal., 2012). In many
megacities, slum area development in peri-urban fringes confines
the urban poor to a choice between low paying jobs near home
or long commuting times for marginally higher wages (Burdett
and Sudjic, 2010). The poor have limited options to change living
locations and can afford few motorized trips, so they predomi-
nantly walk, which disproportionally burdens women and children
(Anand and Tiwari, 2006; Pendakur, 2011). The urban poor in OECD
cities have similar issues (Glaeser, 2011). Reducing vulnerability to
climate change requires integrating the mobility needs of the poor
into planning that can help realize economic and social develop-
ment objectives (Amekudzi etal., 2011; Bowen etal., 2012).
Total transport emissions from non-OECD countries will likely
surpass OECD emissions by 2050 due to motorization, increasing
population and higher travel demand (Figure 8.10). However, esti-
mated average personal travel per capita in non-OECD countries
at will remain below the average in OECD countries. With coun-
tries facing limits to transport infrastructure investment (Arndt
etal., 2012), the rapid mobility trends represents a major chal-
lenge in terms of traffic congestion, energy demand, and related
GHG emissions (IEA, 2012a). Failure to manage the growth of
motorized mobility in the near term will inevitably lead to higher
environmental cost and greater difficulty to control emissions in
the long term (Schäfer etal., 2009; Pietzcker etal., 2013).
A high modal share of public transport use characterizes develop-
ing cities (Estache and GóMez-Lobo, 2005) and this prevalence
is expected to continue (Deng and Nelson, 2011; Cuenot etal.,
2012). However, deficient infrastructure and inadequate services
leads to the overloading of para-transit vans, minibuses, jeeps and
shared taxis and the use of informal transport services (Cervero
and Golub, 2011). By combining technologies, providing new
social arrangements, and incorporating a long-term sustainability
and climate perspective to investment decisions, these services
can be recast and maintained as mobility resources since they
service the poor living in inaccessible areas at affordable prices
(Figueroa etal., 2013). A central strategy that can have multiple
health, climate, environmental, and social benefits is to invest in
the integration of infrastructure systems that connect safe routes
for walking and cycling with local public transport, thus giving it
priority over infrastructure for LDVs that serve only a small share
of the population (Woodcock etal., 2009; Tiwari and Jain, 2012).
Opportunities for strategic sustainable urban transport devel-
opment planning exist that can be critical to develop medium
sized cities where population increases are expected to be large
(Wittneben etal., 2009; ADB, 2012b; Grubler etal., 2012). Vision,
leadership, and a coherent programme for action, adaptation, and
consolidation of key institutions that can harness the energy and
engagement of all stakeholders in a city will be needed to achieve
these goals (Dotson, 2011). Today, more than 150 cities worldwide
have implemented bus rapid transit (BRT) systems. Innovative
features such as electric transit buses (Gong etal., 2012) and the
ambitious high-speed rail expansion in China provide evidence of
a fast process of planning and policy implementation.
642642
Transport
8
Chapter 8
erated pace with which both urbanization and motorization are pro-
ceeding in many non-OECD countries emphasizes serious constraints
and potentially damaging developments. These include road and public
transport systems that are in dire condition; limited technical and finan-
cial resources; the absence of infrastructure governance; poor legal
frameworks; and rights to innovate that are needed to act effectively
and improve capacity competences (Kamal-Chaoui and Plouin, 2012;
Lefèvre, 2012). The outcome is a widening gap between the growth of
detrimental impacts of motorization and effective action (Kane, 2010;
Li, 2011; Vasconcellos, 2011). A highly complex and changing context
with limited data and information further compromise transport sus-
tainability and mitigation in non-OECD countries (Dimitriou, 2006;
Kane, 2010; Figueroa etal., 2013). The relative marginal socio-economic
costs and benefits of various alternatives can be context sensitive with
respect to sustainable development (Amekudzi, 2011). Developing the
analytical and data capacity for multi-objective evaluation and priority
setting is an important part of the process of cultivating sustainability
and mitigation thinking and culture in the long-term.
Potentials for controlling emissions while improving accessibility and
achieving functional mobility levels in the urban areas of rapidly grow-
ing developing countries can be improved with attention to the man-
ner in which the mobility of the masses progresses in their transition
from slower (walking / cycling) to faster motorized modes (Kahn Ribeiro
etal., 2012). A major shift towards the use of mass public transport
guided by sustainable transport principles, including the maintenance
of adequate services and safe infrastructure for non-motorized trans-
port, presents the greatest mitigation potential (Bongardt etal., 2011;
La Branche, 2011). Supporting non-motorized travel can often provide
access and also support development more effectively, more equitably,
and with fewer adverse side-effects, than if providing for motorized
travel (Woodcock etal., 2007). Transport can be an agent of sustained
urban development that prioritizes goals for equity and emphasizes
accessibility, traffic safety, and time savings for the poor with minimal
detriment to the environment and human health, all while reducing
emissions (Amekudzi et al., 2011; Li, 2011; Kane, 2010). The choice
among alternative mitigation measures in the transport sector can
be supported by growing evidence on a large number of co-benefits,
while some adverse side effects exist that need to be addressed or
minimized (see Section 8.7) (Figueroa and Kahn Ribeiro, 2013; Creutzig
and He, 2009; Creutzig etal., 2012a, b; Zusman etal., 2012).
8.10 Sectoral policies
Aggressive policy intervention is needed to significantly reduce fuel
carbon intensity and energy intensity of modes, encourage travel by
the most efficient modes, and cut activity growth where possible and
reasonable (see Sections 8.3 and 8.9). In this section, for each major
transport mode, policies and strategies are briefly discussed by policy
type as regulatory or market-based, or to a lesser extent as informa-
tional, voluntary, or government-provided. A full evaluation of poli-
cies across all sectors is presented in Chapters 14 and 15. Policies to
support sustainable transport can simultaneously provide co-benefits
(Table 8.4) such as improving local transport services and enhanc-
ing the quality of environment and urban living, while boosting both
climate change mitigation and energy security (ECMT, 2004; WBCSD,
2004, 2007; World Bank, 2006; Banister, 2008; IEA, 2009; Bongardt
etal., 2011; Ramani etal., 2011; Kahn Ribeiro etal., 2012). The type
of policies, their timing, and chance of successful implementation are
context dependent (Santos etal., 2010). Diverse attempts have been
made by transport agencies in OECD countries to define and measure
policy performance (OECD, 2000; CST, 2002; Banister, 2008; Ramani
etal., 2011). The mobility needs in non-OECD countries highlight the
importance of placing their climate-related transport policies in the
context of goals for broader sustainable urban development goals (see
Section 8.9; Kahn Ribeiro etal., 2007; Bongardt etal., 2011).
Generally speaking, market-based instruments, such as carbon cap and
trade, are effective at incentivizing all mitigation options simultane-
ously (Flachsland etal., 2011). However, vehicle and fuel suppliers as
well as end-users, tend to react weakly to fuel price signals, such as
fuel carbon taxes, especially for passenger travel (Creutizig etal., 2011;
Yeh and McCollum, 2011). Market policies are economically more effi-
cient at reducing emissions than fuel carbon intensity standards (Hol-
land et al., 2009; Sperling and Yeh, 2010; Chen and Khanna, 2012;
Holland, 2012). However, financial instruments, such as carbon taxes,
must be relatively large to achieve reductions equivalent to those pos-
sible with regulatory instruments. As a result, to gain large emissions
reductions a suite of policy instruments will be needed (NRC, 2011c;
Sperling and Nichols, 2012), including voluntary schemes, which have
been successful in some circumstances, such as for the Japanese airline
industry (Yamaguchi, 2010).
8�10�1 Road transport
A wide array of policies and strategies has been employed in differ-
ent circumstances to restrain private LDV use, promote mass transit
modes, manage traffic congestion and promote new fuels in order to
reduce fossil fuel use, air pollution, and GHG emissions. These policies
and strategies overlap considerably, often synergistically.
The magnitude of urban growth and population redistribution from
rural to urban areas in emerging and developing countries is expected
to continue (see Sections 8.2 and 12.2). This implies a large increase
in demand for motorized transport especially in medium-size cities
(Grubler etal., 2012). In regions and countries presently with low lev-
els of LDV ownership, opportunities exist for local and national gov-
ernments to manage future rising road vehicle demand in ways that
support economic growth, provide broad social benefits (Wright and
Fulton, 2005; IEA, 2009; Kato etal., 2005) and keep GHG emissions
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in bounds. Local history and social culture can help shape the specific
problem, together with equity implications and policy aspirations that
ultimately determine what will become acceptable solutions (Vascon-
cellos, 2001; Dimitriou, 2006; Kane, 2010; Li, 2011; Verma etal., 2011).
Even if non-OECD countries pursue strategies and policies that encour-
age LDV use for a variety of economic, social, and environmental moti-
vations, per capita LDV travel in 2050 could remain far below OECD
countries. However, in many OECD countries, passenger LDV travel
demand per capita appears to have begun to flatten, partly driven
by increasing levels of saturation and polices to manage increased
road transport demand (Section 8.2.1; Millard-Ball and Schipper,
2011; Schipper, 2011; Goodwin, 2012; IEA, 2012c; Meyer etal., 2012).
Even if this OECD trend of slowing growth in LDV travel continues or
even eventually heads downwards, it is unlikely to offset projected
growth in non-OECD LDV travel or emissions because those popula-
tions and economies are likely to continue to grow rapidly along with
LDV ownership. Only with very aggressive policies in both OECD and
non-OECD countries would total global LDV use stabilize in 2050.
This is illustrated in a 2 °C LDV transport scenario generated by Fulton
etal. (2013), using mainly IEA (2012c) data. In that policy scenario,
LDV travel in OECD countries reaches a peak of around 7500 vehicle
km / capita in 2035 then drops by about 20 % by 2050. By comparison,
per capita LDV travel in non-OECD countries roughly quadruples from
an average of around 500 vehicle km / capita in 2012 to about 2000
vehicle km / capita in 2050, remaining well below the OECD average.
Many countries have significant motor fuel taxes that, typically, have
changed little in recent years. This indicates that such a market instru-
ment is not a policy tool being used predominantly to reduce GHG
emissions. The typical approach increasingly being used is a suite of
regulatory and other complementary policies with separate instru-
ments for vehicles and for fuels. The challenge is to make them consis-
tent and coherent. For instance, the fuel efficiency and GHG emission
standards for vehicles in Europe and the United States give multiple
credits to plug-in electric vehicles (PEVs) and fuel cell vehicles (FCVs).
Zero upstream emissions are assigned, although this is technically
incorrect but designed to be an implicit subsidy (Lutsey and Sperling,
2012).
Fuel choice and carbon intensity
10
. Flexible fuel standards that
combine regulatory and market features include the Californian low-
carbon fuel standard (LCFS) (Sperling and Nichols, 2012) and the Euro-
pean Union fuel quality directive (FQD). Fuel carbon intensity reduction
targets for 2020 (10 % for California and 6 % for EU) are expected to
be met by increasing use of low-carbon biofuels, hydrogen, and elec-
tricity. They are the first major policies in the world premised on the
measurement of lifecycle GHG intensities (Yeh and Sperling, 2010;
Creutzig etal., 2011), although implementation of lifecycle analyses
can be challenging and sometimes misleading since it is difficult to
10
The following four sub-sections group policies along the lines of the decomposi-
tion as outlined in 8.1 and Figure 8.2
design implementable rules that fully include upstream emissions
(Lutsey and Sperling, 2012); emissions resulting from induced market
effects; and emissions associated with infrastructure, the manufactur-
ing of vehicles, and the processing and distribution of fuels (for LCA
see Annex II.6.3 Kendall and Price, 2012).
Biofuel policies have become increasingly controversial as more scru-
tiny is applied to the environmental and social equity impacts (Section
11.13). In 2007, the European Union and the United States adopted
aggressive biofuel policies (Yeh and Sperling, 2013). The effectiveness
of these policies remains uncertain, but follow-up policies such as
California’s LCFS and EU’s FQD provide broader, more durable policy
frameworks that harness market forces (allowing trading of credits),
and provide flexibility to industry in determining how best to reduce
fuel carbon intensity. Other related biofuel policies include subsidies
(IEA, 2011d) and mandatory targets (REN21, 2012).
Vehicle energy intensity. The element of transport that shows the
greatest promise of being on a trajectory to achieve large reductions in
GHG emissions by 2050 is reducing the energy and fuel carbon intensi-
ties of LDVs. Policies are being put in place to achieve dramatic
improvements in vehicle efficiency, stimulating automotive companies
to make major investments. Many countries have now adopted aggres-
sive targets and standards (Figure 8.13), with some standards criticized
<Beginpic>
Figure 8�13 | Historic emissions and future (projected and mandated) carbon dioxide
emissions targets for LDVs in selected countries and European Union, normalized by
using the same New European Driving Cycle (NDEC) that claims to represent real-world
driving conditions. Source: ICCT (2007, 2013)
Notes: (1) China’s target reflects gasoline LDVs only and may become higher if new
energy vehicles are considered. (2) Gasoline in Brazil contains 22 % ethanol but data
here are converted to 100 % gasoline equivalent.
USA
Canada
Poposed Targets or
Targets under Study
Enacted Targets
Historical PerformanceEU
Australia
Japan
ChinaSouth Korea
India
Mexico
2005 2010 20202015 20252000
50
100
150
200
250
LDV Emission Efficiency [gCO
2
/km]
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for not representing real-world conditions (Mock etal., 2012). Most
are developed countries, but some emerging economies, including
China and India, are also adopting increasingly aggressive standards
(Wang etal., 2010).
Regulatory standards focused on fuel consumption and GHG emissions
vary in their design and stringency. Some strongly stimulate reductions
in vehicle size (as in Europe) and others provide strong incentives to
reduce vehicle weight (as in the United States) (CCC, 2011). All have
different reduction targets. As of April 2010, 17 European countries
had implemented taxes on LDVs wholly or partially related to CO
2
emissions. Regulatory standards require strong market instruments
and align market signals with regulations as they become tighter
over time. Examples are fuel and vehicle purchase taxes and circula-
tion taxes that can limit rebound effects. Several European countries
have established revenue-neutral feebate schemes (a combination of
rebates awarded to purchasers of low carbon emission vehicles and
fees charged to purchasers of less efficient vehicles) (Greene and Plot-
kin, 2011). Annual registration fees can have similar effects if linked
directly with carbon emissions or with related vehicle attributes such
as engine displacement, engine power, or vehicle weight (CARB, 2012).
One concern with market-based policies is their differential impact
across population groups such as farmers needing robust vehicles to
traverse rugged terrain and poor quality roads. Equity adjustments can
be made so that farmers and large families are not penalized for hav-
ing to buy a large car or van (Greene and Plotkin, 2011).
Standards are likely to spur major changes in vehicle technology, but
in isolation are unlikely to motivate significant shifts away from petro-
leum-fuelled ICE vehicles. In the United States, a strong tightening of
standards through to 2025 is estimated to trigger only a 1 % market
share for PEVs if only economics is considered (EPA, 2011).
A more explicit regulatory instrument to promote EVs and other new,
potentially very-low carbon propulsion technologies is a zero emis-
sion vehicle mandate, as originally adopted by California in 1990 to
improve local air quality, and which now covers almost 30 % of the
United States market. This policy, now premised on reducing GHGs,
requires about 15 % of new vehicles in 2025 to be a mix of PEVs and
FCVs (CARB, 2012).
There are large potential efficiency improvements possible for medium
and heavy-duty vehicles (HDVs) (see Section 8.3.1.2), but policies to
pursue these opportunities have lagged those for LDVs. Truck types,
loads, applications, and driving cycles are much more varied than for
LDVs and engines are matched with very different designs and loads,
thereby complicating policy-making. However, China implemented
fuel consumption limits for HDVs in July 2012 (MIIT, 2011); in 2005
Japan set modest fuel efficiency standards to be met by 2015 (Ata-
bani etal., 2011); California, in 2011, required compulsory retrofits to
reduce aerodynamic drag and rolling resistance (Atabani etal., 2011);
the United States adopted standards for new HDVs and buses manu-
factured from 2014 to 2018 (Greene and Plotkin, 2011); and the EU
intends to pursue similar actions including performance standards and
fuel efficiency labelling by 2014 (Kojima and Ryan, 2010). Aggressive
air pollution standards since the 1990s for NO
x
and particulate matter
emissions from HDVs in many OECD countries have resulted in a fuel
consumption penalty in the past of 7 % to 10 % (IEA, 2009; Tourlonias
and Koltsakis, 2011). However, emission technology improvements and
reductions in black carbon emissions, which strongly impact climate
change (see Section 8.2.2.1), will offset some of the negative effect of
this increased fuel consumption.
Activity reduction. A vast and diverse mix of policies is used to restrain
and reduce the use of LDVs, primarily by focusing on land use patterns,
public transport options, and pricing. Other policy strategies to reduce
activity include improving traffic management (Barth and Boriboonsom-
sin, 2008), better truck routing systems (Suzuki, 2011), and smart real-
time information to reduce time searching for a parking space. Greater
support for innovative services using information and communication
technologies, such as dynamic ride sharing and demand-responsive
para-transit services (see Section 8.4), creates still further opportunities
to shift toward more energy efficient modes of travel.
Policies can be effective at reducing dependence on LDVs as shown
by comparing Shanghai with Beijing, which has three times as many
LDVs even though the two cities have similar levels of affluence, the
same culture, and are of a similar population (Hao etal., 2011). Shang-
hai limited the ownership of LDVs by establishing an expensive license
auction, built fewer new roads, and invested more in public transport,
whereas Beijing built an extensive network of high capacity express-
ways and did little to restrain car ownership or use until recently. The
Beijing city administration has curtailed vehicle use by forbidding cars
to be used one day per week since 2008, and sharply limited the num-
ber of new license plates issued each year since 2011 (Santos etal.,
2010) Hao etal., 2011). The main aims to reduce air pollution, traffic
congestion, and costs of road infrastructure exemplify how policies to
reduce vehicle use are generally, but not always, premised on non-GHG
co-benefits. European cities have long pursued demand reduction strat-
egies, with extensive public transport supply, strict growth controls,
and more recent innovations such as bicycle sharing. California seeks
to create more liveable communities by adopting incentives, policies,
and rules to reduce vehicle use, land use sprawl, and GHG emissions
from passenger travel. The California law calls for 6 – 8 % reduction in
GHG emissions from passenger travel per capita (excluding changes
in fuel carbon intensity and vehicle energy intensity) in major cities by
2020, and 13 – 16 % per capita by 2035 (Sperling and Nichols, 2012).
The overall effectiveness of initiatives to reduce or restrain road vehicle
use varies dramatically depending on local commitment and local cir-
cumstances, and the ability to adopt synergistic policies and practices by
combining pricing, land use management, and public transport measures.
A broad mix of policies successfully used to reduce vehicle use in OECD
countries, and to restrain growth in emerging economies, includes pric-
ing to internalize energy, environmental, and health costs; strengthening
land use management; and providing more and better public transport.
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Policies to reduce LDV activity can be national, but mostly they are local,
with the details varying from one local administration to another.
Some policies are intrinsically more effective than others. For instance,
fuel taxes will reduce travel demand but drivers are known to be rela-
tively inelastic in their response (Hughes etal., 2006; Small and van
Dender, 2007). However, drivers are more elastic when price increases
are planned and certain (Sterner, 2007). Pricing instruments such as
congestion charges, vehicle registration fees, road tolls and parking
management can reduce LDV travel by inducing trip chaining, modal
shifts, and reduced use of cars (Litman, 2006). Policies and practices
of cities in developing countries can be influenced by lending prac-
tices of development banks, such as the Rio+20 commitment to spend
approximately 170 billion USD
2010
on more sustainable transport proj-
ects, with a focus on Asia (ADB, 2012c).
System efficiency. Improvements have been far greater in freight
transport and aviation than for surface passenger transport (rail and
road). Freight transport has seen considerable innovation in container-
ization and intermodal connections, as has aviation, though the effects
on GHG emissions are uncertain (and could be negative because of
just-in-time inventory management practices). For surface passenger
travel, efforts to improve system efficiency and inter-modality are hin-
dered by conflicting and overlapping jurisdictions of many public and
private sector entities and tensions between fiscal, safety, and equity
goals. Greater investment in roads than in public transport occurred in
most cities of developed countries through the second half of the 20th
century (Owens, 1995; Goodwin, 1999). The 21st century, though, has
seen increasing government investment in bus rapid transit and rail
transit in OECD countries (Yan and Crookes, 2010; Tennøy, 2010) along
with increasing support for bicycle use.
Since the 1960s, many cities have instigated supportive policies and
infrastructure that have resulted in a stable growth in cycling (Servaas,
2000; Hook, 2003; TFL, 2007; NYC, 2012). Several European cities have
had high cycle transport shares for many years, but now even in Lon-
don, UK, with efficient public transport systems, the 2 % cycle share
of travel modes is targeted to increase to 5 % of journeys in 2026 as
a result of a range of new policies (TFL, 2010). However, in less devel-
oped cities such as Surabaya, Indonesia, 10 % of total trips between
1 – 3 km are already by cycling (including rickshaws) in spite of unsup-
portive infrastructure and without policies since there are few afford-
able alternatives (Hook, 2003). Where cycle lanes have been improved,
as in Delhi, greater uptake of cycling is evident (Tiwari and Jain, 2012).
8�10�2 Rail transport
Rail transport serves 28 billion passengers globally, carrying them
around 2500 billion p-km / yr
11
. Rail also carries 11.4 billion tonne of
11
By way of comparison, aviation moves 2.1 billion passengers globally (some 3900
billion p-km / yr).
freight (8845 billion t-km / yr) (Johansson etal., 2012). Policies to fur-
ther improve system efficiency may improve competitiveness and
opportunities for modal shift to rail (Johansson etal., 2012). Specific
energy and carbon intensities of rail transport are relatively small com-
pared to some other modes (see Section 8.3). System efficiency can
also be assisted through train driver education and training policies
(Camagni etal., 2002).
Fuel intensity. Roughly one third of all rail transport is driven by die-
sel and two-thirds by electricity (Johansson etal., 2012). Policies to
reduce fuel carbon intensity are therefore linked to a large extent to
those for decarbonizing electricity production (Chapter 7; DLR, 2012).
For example, Sweden and Switzerland are running their rail systems
using very low carbon electricity (Gössling, 2011).
Energy intensity. Driven largely by corporate strategies, the energy
intensity of rail transport has been reduced by more than 60 %
between 1980 and 2001 in the United States (Sagevik, 2006). Overall
reduction opportunities of 45 – 50 % are possible for passenger trans-
port in the EU and 40 – 50 % for freight (Andersson etal., 2011). Recent
national policies in the United Kingdom and Germany appear to have
resulted in 73 % rail freight growth over the period 1995 – 2007, partly
shifted from road freight.
System efficiency. China, Europe, Japan, Russia, United States and
several Middle-eastern and Northern African countries continue (or are
planning) to invest in high-speed rail (HSR) (CRC, 2008). It is envis-
aged that the worldwide track length of about 15,000 km in 2012 will
nearly triple by 2025 due to government supporting policies, allowing
HSR to better compete with medium haul aviation (UIC, 2012).
8�10�3 Waterborne transport
Although waterborne transport is comparatively efficient in terms of
gCO
2
/ t-km compared to other freight transport modes (see Section
8.6), the International Maritime Organization (IMO) has adopted man-
datory measures to reduce GHG emissions from international shipping
(IMO, 2011). This is the first mandatory GHG reduction regime for an
international industry sector and for the standard to be adopted by all
countries is a model for future international climate change co-opera-
tion for other sectors (Yamaguchi, 2012). Public policies on emissions
from inland waterways are nationally or regionally based and currently
focus more on the reduction of NO
x
and particulate matter than on
CO
2
. However, policy measures are being considered to reduce the
carbon intensity of this mode including incentives to promote ‘smart
steaming’, upgrade to new, larger vessels, and switch to alternative
fuels, mainly LNG (Panteia, 2013). Few if any, policies support the use
of biofuels, natural gas or hydrogen for small waterborne craft around
coasts or inland waterways and little effort has been made to assess
the financial implications of market (and other) policies on developing
countries who tend to import and export low value-to-weight prod-
ucts, such as food and extractible resources (Faber etal., 2012).
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Energy intensity� IMO’s Energy Efficiency Design Index (EEDI) is to
be phased in between 2013 and 2025. It aims to improve the energy
efficiency of certain categories of new ships and sets technical stan-
dards (IMO, 2011). However, the EEDI may not meet the target if ship-
ping demand increases faster than fuel carbon and energy intensi-
ties improve. The voluntary Ship Energy Efficiency Management Plan
(SEEMP) was implemented in 2013 (IMO, 2011). For different ship
types and sizes it provides a minimum energy efficiency level. As much
as 70 % reduction of emissions from new ships is anticipated with the
aim to achieve approximately 25 – 30 % reductions overall by 2030
compared with business-as-usual (IISD, 2011). It is estimated that, in
combination, EEDI requirements and SEEMP will cut CO
2
emissions
from shipping by 13 % by 2020 and 23 % by 2030 compared to a ‘no
policy’ baseline (Lloyds Register and DNV, 2011).
8�10�4 Aviation
After the Kyoto Protocol directed parties in Annex I to pursue inter-
national aviation GHG emission limitation / reduction working through
the International Civil Aviation Organization (ICAO) (Petersen, 2008),
member states are working together with the industry towards vol-
untarily improving technologies, increasing the efficient use of air-
port infrastructure and aircraft, and adopting appropriate economic
measures (ICAO, 2007b; ICAO, 2010a). In 2010, ICAO adopted global
aspirational goals for the international aviation sector to improve fuel
efficiency by an average of 2 % per annum until 2050 and to keep
its global net carbon emissions from 2020 at the same level (ICAO,
2010b). These goals exceed the assumptions made in many scenarios
(Mayor and Tol, 2010).
Policy options in place or under consideration include regulatory
instruments (fuel efficiency and emission standards at aircraft or sys-
tem levels); market-based approaches (emission trading under caps,
fuel taxes, emission taxes, subsidies for fuel efficient technologies);
and voluntary measures including emission offsets (Daley and Preston,
2009). Environmental capacity constraints on airports also exist and
may change both overall volumes of air transport and modal choice
(Upham et al., 2004; Evans, 2010). National policies affect mainly
domestic aviation, which covers about 30 – 35 % of total air transport
(IATA, 2009; Lee etal., 2009; Wood etal., 2010). A nationwide cap-
and-trade policy could have the unintended consequence of slow-
ing aircraft fleet turnover and, through diverted revenue, of delaying
technological upgrades, which would slow GHG reductions, though
to what degree is uncertain (Winchester etal., 2013). In the UK, an
industry group including airport companies, aircraft manufacturers and
airlines has developed a strategy for reducing GHG emissions across
the industry (Sustainable Aviation, 2012).
The EU is currently responsible for 35 % of global aviation emissions.
The inclusion of air transport in the EU emission trading scheme (ETS)
is the only binding policy to attempt to mitigate emissions in this sec-
tor (Anger, 2010; Petersen, 2008; Preston etal., 2012). The applica-
bility of ETS policy to non-European routes (for flights to and from
destinations outside the EU) (Malina etal., 2012) has been delayed
for one year, but the directive continues to apply to flights between
destinations in the EU following a proposal by the European Com-
mission in November 2012 in anticipation of new ICAO initiatives
towards a global market-based mechanism for all aviation emissions
(ICAO, 2012).
Taxing fuels, tickets, or emissions may reduce air transport volume
with elasticities varying between – 0.3 to – 1.1 at national and inter-
national levels, but with strong regional differences (Europe has 40 %
stronger elasticities than most other world regions, possibly because
of more railway options). Airport congestion adds considerable emis-
sions (Simaiakis and Balakrishnan, 2010) and also tends to moderate
air transport demand growth to give a net reduction of emissions at
network level (Evans and Schäfer, 2011).
Fuel carbon intensity. Policies do not yet exist to introduce low-car-
bon biofuels. However, the projected GHG emission reductions from
the possible future use of biofuels, as assumed by the aviation indus-
try, vary between 19 % of its adopted total emission reduction goal
(Sustainable Aviation, 2008) to over 50 % (IATA, 2009),depending on
the assumptions made for the other reduction options that include
energy efficiency, improved operation and trading emission permits.
Sustainable production issues also apply (see Section 8.3.3).
Energy intensity. The energy efficiency of aircraft has improved his-
torically without any policies in force, but with the rate of fuel con-
sumption reducing over time from an initial 3 – 6 % in the 1950s to
between 1 % and 2 % per year at the beginning of the 21st century
(Pulles etal., 2002; Fulton and Eads, 2004; Bows etal., 2005; Peeters
and Middel, 2007; Peeters etal., 2009). This slower rate of fuel reduc-
tion is possibly due to increasing lead-times required to develop, cer-
tify, and introduce new technology (Kivits etal., 2010).
System efficiency. The interconnectedness of aviation services can
be a complicating factor in adopting policies, but also lends itself to
global agreements. For example, regional and national air traffic con-
trollers have the ability to influence operational efficiencies. The use
of market policies to reduce GHG emissions is compelling because
it introduces a price signal that influences mitigation actions across
the entire system. But like other aspects of the passenger transport
system, a large price signal is needed with aviation fuels to gain sig-
nificant reductions in energy use and emissions (Tol, 2007; Peeters
and Dubois, 2010; OECD and UNEP, 2011). Complementary policies to
induce system efficiencies include measures to divert tourists to more
efficient modes such as high-speed rail. However, since short- and
medium-haul aircraft now have similar energy efficiencies per passen-
ger km compared to LDVs (Figure 8.6), encouraging people to take
shorter journeys (hence by road instead of by air), thereby reducing
tourism total travel, has become more important (Peeters and Dubois,
2010). No country has adopted a low-carbon tourism strategy (OECD
and UNEP, 2011).
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8�10�5 Infrastructure and urban planning
Urban form has a direct effect on transport activity (see Section 12.4).
As a consequence, infrastructure policies and urban planning can pro-
vide major contributions to mitigation (see Section 12.5). A modal shift
from LDVs to other surface transport modes could be partly incentiv-
ized by policy measures that impose physical restrictions as well as
pricing regimes. For example, LDV parking management is a simple
form of cost effective, pricing instrument (Barter etal., 2003; Litman,
2006). Dedicated bus lanes, possibly in combination with a vehicle
access charge for LDVs, can be strong instruments to achieving rapid
shifts to public transport (Creutzig and He, 2009).
Policies that support the integration of moderate to high density
urban property development with transit-oriented development strat-
egies that mix residential, employment, and shopping facilities can
encourage pedestrians and cyclists, thereby giving the dual benefits of
reducing car dependence and preventing urban sprawl (Newman and
Kenworthy, 1996; Cervero, 2004; Olaru etal., 2011). GHG emissions
savings (Trubka etal., 2010a; Trubka etal., 2010b) could result in co-
benefits of health, productivity, and social opportunity (Trubka etal.,
2010c; Ewing and Cervero, 2010; Höjer etal., 2011) if LDV trips could
be reduced using polycentric city design and comprehensive smart-
growth policies (Dierkers etal., 2008). Policies to support the building
of more roads, airports, and other infrastructure can help relieve con-
gestion in the short term, but can also induce travel demand (Duranton
and Turner, 2011) and create GHG emissions from construction (Ches-
ter and Horvath, 2009).
8.11 Gaps in knowledge
and data
The following gaps made assessing the mitigation potential of the
transport sector challenging.
Gaps in the basic statistics are still evident on the costs and energy
consumption of freight transport, especially in developing countries.
• Data and understanding relating to freight logistical systems and
their economic implications are poor, as are the future effects
on world trade of decarbonization and climate change impacts.
Hence, it is difficult to design new low-carbon freight policies.
• Future technological developments and costs of batteries, fuel
cells, and vehicle designs are uncertain.
• The infrastructure requirement for new low-carbon transport fuels
is poorly understood.
• Cost of components for novel vehicle powertrains cannot be deter-
mined robustly since rates of learning, cost decreases, and associ-
ated impacts are unknown.
• Assessments of mitigating transport GHG emissions, the global
potential, and costs involved are inconsistent.
• Prices of crude oil products fluctuate widely as do those for alter-
native transport fuels, leading to large variations in scenario mod-
elling assumptions.
• A better knowledge of consumer travel behaviour is needed, par-
ticularly for aviation.
• Limited understanding exists of how and when people will choose
to buy and use new types of low-carbon vehicles or mobility ser-
vices (such as demand responsive transit or car-share).
• There are few insights of behavioural economics to predict mobility
systematically and whether producers will incorporate low-carbon
technologies that may not maximize profit.
• How travellers will respond to combinations of low-carbon strat-
egies (mixes of land use, transit, vehicle options) is especially
important for fast-growing, developing countries where alternative
modes to the car-centric development path could be deployed, is
unknown.
• Understanding how low-carbon transport and energy technologies
will evolve (via experience curves and innovation processes) is not
well developed. Most vehicles rely on stored energy, so there is
a need to better understand the cost and energy density of non-
hydrocarbon energy storage mediums, such as batteries, super-
capacitors and pressure vessels.
• Decoupling of transport GHG from economic growth needs further
elaboration, especially the policy frameworks that can enable this
decoupling to accelerate in both OECD and non-OECD nations.
• The rate of social acceptance of innovative concepts such as LDV
road convoys, induction charging of electric vehicles, and driver-
less cars (all currently being demonstrated) is difficult to predict, as
is the required level of related infrastructure investments. Recent
rapid developments in metro systems in several cities illustrate
how quickly new transport systems can be implemented when the
demand, policies, and investments all come together and public
support is strong.
8.12 Frequently Asked
Questions
FAQ 8�1 How much does the transport sector
contribute to GHG emissions and how is
this changing?
The transport sector is a key enabler of economic activity and social
connectivity. It supports national and international trade and a large
global industry has evolved around it. Its greenhouse gas (GHG) emis-
sions are driven by the ever-increasing demand for mobility and move-
ment of goods. Together, the road, aviation, waterborne, and rail trans-
port sub-sectors currently produce almost one quarter of total global
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energy-related CO
2
emissions [Section 8.1]. Emissions have more than
doubled since 1970 to reach 7.0 Gt CO
2
eq by 2010 with about 80 % of
this increase coming from road vehicles. Black carbon and other aero-
sols, also emitted during combustion of diesel and marine oil fuels, are
relatively short-lived radiative forcers compared with carbon dioxide
and their reduction is emerging as a key strategy for mitigation [8.2].
Demands for transport of people and goods are expected to continue
to increase over the next few decades [8.9]. This will be exacerbated
by strong growth of passenger air travel worldwide due to improved
affordability; by the projected demand for mobility access in non-OECD
countries that are starting from a very low base; and by projected
increases in freight movements. A steady increase of income per capita
in developing and emerging economies has already led to a recent
rapid growth in ownership and use of 2-wheelers, 3-wheelers and light
duty vehicles (LDVs), together with the development of new transport
infrastructure including roads, rail, airports, and ports.
Reducing transport emissions will be a daunting task given the inevi-
table increases in demand. Based on continuing current rates of growth
for passengers and freight, and if no mitigation options are implemented
to overcome the barriers [8.8], the current transport sector’s GHG emis-
sions could increase by up to 50 % by 2035 at continued current rates
of growth and almost double by 2050 [8.9]. An increase of transport’s
share of global energy-related CO
2
emissions would likely result. How-
ever, in spite of lack of progress in many countries to date, new vehicle
and fuel technologies, appropriate infrastructure developments including
for non-motorized transport in cities, transport policies, and behavioural
changes could begin the transition required [8.3, 8.4, 8.9].
FAQ 8�2 What are the main mitigation options
and potentials for reducing GHG
emissions?
Decoupling transport from GDP growth is possible but will require
the development and deployment of appropriate measures, advanced
technologies, and improved infrastructure. The cost-effectiveness of
these opportunities may vary by region and over time [8.6]. Delivering
mitigation actions in the short-term will avoid future lock-in effects
resulting from the slow turnover of stock (particularly aircraft, trains,
and ships) and the long-life and sunk costs of infrastructure already in
place [8.2, 8.4].
When developing low-carbon transport systems, behavioural change and
infrastructure investments are often as important as developing more
efficient vehicle technologies and using lower-carbon fuels [8.1, 8.3].
• Avoidance: Reducing transport activity can be achieved by avoid-
ing unnecessary journeys, (for example by tele-commuting and
internet shopping), and by shortening travel distances such as
through the densification and mixed-zoning of cities.
• Modal choice: Shifting transport options to more efficient modes
is possible, (such as from private cars to public transport, walking,
and cycling), and can be encouraged by urban planning and the
development of a safe and efficient infrastructure.
• Energy intensity: Improving the performance efficiency of air-
craft, trains, boats, road vehicles, and engines by manufacturers
continues while optimizing operations and logistics (especially for
freight movements) can also result in lower fuel demand.
• Fuel carbon intensity: Switching to lower carbon fuels and
energy carriers is technically feasible, such as by using sustain-
ably produced biofuels or electricity and hydrogen when produced
using renewable energy or other low-carbon technologies.
These four categories of transport mitigation options tend to be inter-
active, and emission reductions are not always cumulative. For exam-
ple, an eco-driven, hybrid LDV, with four occupants, and fuelled by a
low-carbon biofuel would have relatively low emissions per passenger
kilometre compared with one driver travelling in a conventional gaso-
line LDV. But if the LDV became redundant through modal shift to pub-
lic and non-motorized transport, the overall emission reductions could
only be counted once.
Most mitigation options apply to both freight and passenger trans-
port, and many are available for wide deployment in the short term
for land, air, and waterborne transport modes, though not equally and
at variable costs [8.6]. Bus rapid transit, rail, and waterborne modes
tend to be relatively carbon efficient per passenger or tonne kilometre
compared with LDV, HDV, or aviation, but, as for all modes, this varies
with the vehicle occupancy rates and load factors involved. Modal
shift of freight from short- and medium-haul aircraft and road trucks
to high-speed rail and coastal shipping often offers large mitigation
potential [Table 8.3]. In addition, opportunities exist to reduce the
indirect GHG emissions arising during the construction of infrastruc-
ture; manufacture of vehicles; and extraction, processing, and delivery
of fuels.
The potentials for various mitigation options vary from region to
region, being influenced by the stage of economic development, sta-
tus and age of existing vehicle fleet and infrastructure, and the fuels
available in the region. In OECD countries, transport demand reduc-
tion may involve changes in lifestyle and the use of new informa-
tion and communication technologies. In developing and emerging
economies, slowing the rate of growth of using conventional trans-
port modes with relatively high-carbon emissions for passenger and
freight transport by providing affordable, low-carbon options could
play an important role in achieving global mitigation targets. Poten-
tial GHG emissions reductions from efficiency improvements on new
vehicle designs in 2030 compared with today range from 40 – 70 % for
LDVs, 30 – 50 % for HDVs, up to 50 % for aircraft, and for new ships
when combining technology and operational measures, up to 60 %
[Table 8.3].
649649
Transport
8
Chapter 8
Policy options to encourage the uptake of such mitigation options
include implementing fiscal incentives such as fuel and vehicle taxes,
developing standards on vehicle efficiency and emissions, integrating
urban and transport planning, and supporting measures for infrastruc-
ture investments to encourage modal shift to public transport, walk-
ing, and cycling [8.10]. Pricing strategies can reduce travel demands
by individuals and businesses, although successful transition of the
sector may also require strong education policies that help to create
behavioural change and social acceptance. Fuel and vehicle advances
in the short to medium term will largely be driven through research
investment by the present energy and manufacturing industries that
are endeavouring to meet existing policies as well as to increase their
market shares. However, in order to improve upon this business-as-
usual scenario and significantly reduce GHG emissions across the sec-
tor in spite of the rapidly growing demand, more stringent policies will
be needed. To achieve an overall transition of the sector will require
rapid deployment of new and advanced technology developments,
construction of new infrastructure, and the stimulation of acceptable
behavioural changes.
FAQ 8�3 Are there any co-benefits associated
with mitigation actions?
Climate change mitigation strategies in the transport sector can result
in many co-benefits [8.7]. However, realizing these benefits through
implementing those strategies depends on the regional context in
terms of their economic, social, and political feasibility as well as hav-
ing access to appropriate and cost-effective advanced technologies.
In developing countries where most future urban growth will occur,
increasing the uptake, comfort, and safety of mass transit and non-
motorized transport modes can help improve mobility. In least devel-
oping countries, this may also improve access to markets and therefore
assist in fostering economic and social development. The opportunities
to shape urban infrastructure and transport systems to gain greater
sustainability in the short- to medium-terms are also likely to be higher
in developing and emerging economies than in OECD countries where
transport systems are largely locked-in [8.4].
A reduction in LDV travel and ownership has been observed in sev-
eral cities in OECD countries, but demand for motorized road transport,
including 2- and 3-wheelers, continues to grow in non-OECD nations
where increasing local air pollution often results. Well-designed pol-
icy packages can help lever the opportunities for exploiting welfare,
safety, and health co-benefits [8.10]. Transport strategies associated
with broader policies and programmes can usually target several pol-
icy objectives simultaneously. The resulting benefits can include lower
travel costs, improved mobility, better community health through
reduced local air pollution and physical activities resulting from non-
motorized transport, greater energy security, improved safety, and
time savings through reduction in traffic congestion.
A number of studies suggest that the direct and indirect benefits of
sustainable transport measures often exceed the costs of their imple-
mentation [8.6, 8.9]. However, the quantification of co-benefits and
the associated welfare effects still need accurate measurement. In
all regions, many barriers to mitigation options exist [8.8], but a wide
range of opportunities are available to overcome them and give deep
carbon reductions at low marginal costs in the medium- to long-term
[8.3, 8.4, 8.6, 8.9]. Decarbonizing the transport sector will be challeng-
ing for many countries, but by developing well-designed policies that
incorporate a mix of infrastructural design and modification, techno-
logical advances, and behavioural measures, co-benefits can result and
lead to a cost-effective strategy.
650650
Transport
8
Chapter 8
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